The document summarizes Kun Zhou's PhD research on emotional voice conversion with non-parallel data at the National University of Singapore. It introduces emotional voice conversion and its challenges, including the lack of parallel training data. It then summarizes Kun's publications, which propose CycleGAN-based and VAW-GAN approaches to model prosody for speaker-dependent and independent emotional voice conversion. One publication introduces a method for transferring both seen and unseen emotional styles using a pre-trained speech emotion recognizer to describe emotional styles.
The document outlines conventions commonly found in action films based on a mind map created after watching trailers for Inception, The Dark Knight, and iRobot. These conventions include a mission to be completed, weapons like knives and guns, fights set in a modern big city, motives for characters' actions, futuristic vehicles, good guys and bad guys, explosions and crashes, high-tech machinery, cat-and-mouse chases, outbreaks of destruction, killings and death of loved ones, and suspenseful music.
1) Genre is important for both film producers and audiences. Producers use genre to engage target audiences and be successful, while audiences need to be interested in a genre to watch and enjoy a film.
2) Genre theory is used to categorize films based on factors like storyline, director, and audience expectations. It provides a shortcut for describing films.
3) Genres can change over time as different social groups and audiences emerge with different interests. For example, westerns were once very popular but new genres like sci-fi and thrillers developed.
The document discusses the typical conventions used in science fiction trailers and films. It outlines elements like futuristic technology, conflict between good and evil, and dystopian societies that are commonly seen in the sci-fi genre. It also describes visual and technical conventions regarding costumes, props, camerawork, editing, sound design and music that sci-fi films employ to set the atmosphere and advance the story.
This document provides an overview of a GCSE Film Studies course. It discusses the course structure, which is divided into two exams and two coursework assignments. The exams will include analyzing an unseen film extract and discussing themes in Bend it Like Beckham. The coursework consists of analyzing a film of the student's choice and producing a short film. The document also outlines the objectives for one class, which are to introduce key film terms like genre and analyze how meaning is created through elements like mise-en-scene, cinematography, sound, and editing. Students will watch a horror film scene and discuss which elements make it a horror genre film and how the technical elements create meaning.
The document provides an analysis of the opening title sequence of the film "The Conjuring". It summarizes that the sequence uses grainy photos of the real Perron family and investigators Ed and Lorraine Warren to set up the story and connote that supernatural spirits will play a role. Throughout, the camera remains fixed to build tension and sound effects like crow noises are used to emphasize the dramatic tone. Disturbing images such as the Annabelle doll are also included to create an unsettling atmosphere.
Comedy sketches typically take place in bright, social settings filmed with naturalistic camerawork. Sound and lighting aim to create a realistic environment, with clear dialogue and bright colors used. Props are important, especially those that can cause harm in slapstick scenes. Characters usually include idiotic people contrasted with normals, or very intelligent people who are socially awkward around normals. Sarcasm is also a common trait.
Opening analysis of this is england Luke O'Donnellhaverstockmedia
The opening scene of This is England is a collection of news clips from 1980s Britain set to the song "54-46 Was My Number" by Toots & The Maytals. The clips show the impact of Margaret Thatcher's policies on different groups in British society. While the song is about Jamaica, it emphasizes the popularity of reggae in UK youth culture at the time. White text titles are overlaid on the black-and-white clips to introduce the film and director while maintaining the authenticity of the original footage and creating a smooth pacing for the opening sequence.
Todorov, Propp & Levi Strauss narrative theoriesemclem
The document discusses three classic narrative theories:
1. Todorov's narrative structure suggests stories follow five stages: equilibrium, disruption, recognition, attempt to repair, new equilibrium.
2. Propp identified 8 character types (hero, villain, donor, etc.) and 31 narrative functions (prohibition, punishment, etc.) that move stories along.
3. Levi-Strauss argued binary oppositions (good/evil, men/women, etc.) are key to narrative meaning and stories can only end by resolving conflicts between oppositions.
The document outlines conventions commonly found in action films based on a mind map created after watching trailers for Inception, The Dark Knight, and iRobot. These conventions include a mission to be completed, weapons like knives and guns, fights set in a modern big city, motives for characters' actions, futuristic vehicles, good guys and bad guys, explosions and crashes, high-tech machinery, cat-and-mouse chases, outbreaks of destruction, killings and death of loved ones, and suspenseful music.
1) Genre is important for both film producers and audiences. Producers use genre to engage target audiences and be successful, while audiences need to be interested in a genre to watch and enjoy a film.
2) Genre theory is used to categorize films based on factors like storyline, director, and audience expectations. It provides a shortcut for describing films.
3) Genres can change over time as different social groups and audiences emerge with different interests. For example, westerns were once very popular but new genres like sci-fi and thrillers developed.
The document discusses the typical conventions used in science fiction trailers and films. It outlines elements like futuristic technology, conflict between good and evil, and dystopian societies that are commonly seen in the sci-fi genre. It also describes visual and technical conventions regarding costumes, props, camerawork, editing, sound design and music that sci-fi films employ to set the atmosphere and advance the story.
This document provides an overview of a GCSE Film Studies course. It discusses the course structure, which is divided into two exams and two coursework assignments. The exams will include analyzing an unseen film extract and discussing themes in Bend it Like Beckham. The coursework consists of analyzing a film of the student's choice and producing a short film. The document also outlines the objectives for one class, which are to introduce key film terms like genre and analyze how meaning is created through elements like mise-en-scene, cinematography, sound, and editing. Students will watch a horror film scene and discuss which elements make it a horror genre film and how the technical elements create meaning.
The document provides an analysis of the opening title sequence of the film "The Conjuring". It summarizes that the sequence uses grainy photos of the real Perron family and investigators Ed and Lorraine Warren to set up the story and connote that supernatural spirits will play a role. Throughout, the camera remains fixed to build tension and sound effects like crow noises are used to emphasize the dramatic tone. Disturbing images such as the Annabelle doll are also included to create an unsettling atmosphere.
Comedy sketches typically take place in bright, social settings filmed with naturalistic camerawork. Sound and lighting aim to create a realistic environment, with clear dialogue and bright colors used. Props are important, especially those that can cause harm in slapstick scenes. Characters usually include idiotic people contrasted with normals, or very intelligent people who are socially awkward around normals. Sarcasm is also a common trait.
Opening analysis of this is england Luke O'Donnellhaverstockmedia
The opening scene of This is England is a collection of news clips from 1980s Britain set to the song "54-46 Was My Number" by Toots & The Maytals. The clips show the impact of Margaret Thatcher's policies on different groups in British society. While the song is about Jamaica, it emphasizes the popularity of reggae in UK youth culture at the time. White text titles are overlaid on the black-and-white clips to introduce the film and director while maintaining the authenticity of the original footage and creating a smooth pacing for the opening sequence.
Todorov, Propp & Levi Strauss narrative theoriesemclem
The document discusses three classic narrative theories:
1. Todorov's narrative structure suggests stories follow five stages: equilibrium, disruption, recognition, attempt to repair, new equilibrium.
2. Propp identified 8 character types (hero, villain, donor, etc.) and 31 narrative functions (prohibition, punishment, etc.) that move stories along.
3. Levi-Strauss argued binary oppositions (good/evil, men/women, etc.) are key to narrative meaning and stories can only end by resolving conflicts between oppositions.
Iranian cinema has changed rapidly after the Iranian New Wave, so its better to have some ideas on this topic which I have collected from various books, research papers and journals.
Media key terms revision slides shots angles movement compositionMissConnell
The document defines various camera shots including establishing shots, close-ups, and point-of-view shots. It also explains different camera angles such as low angles and high angles. Finally, it covers compositional techniques for filming including symmetry, the rule of thirds, and manipulating the depth of field through shallow or deep focus.
The early history of film editing developed from single unedited shots by the Lumiere Brothers to more advanced techniques pioneered by Georges Melies, Edwin Porter, and others. Porter made one of the first films to tell a story through editing in 1903 with "The Life of an American Fireman." Russian filmmakers like Lev Kuleshov and Sergei Eisenstein experimented with editing to manipulate emotions and ideas, influencing others. D.W. Griffith's 1915 film "The Birth of a Nation" was a landmark as the first feature-length film to utilize varied camera angles and editing. Advances continued with filmmakers like Murnau and devices like the Moviola, revolutionizing the art of film editing.
Intertextuality refers to how a text draws meaning from other texts through techniques like allusion, quotation, translation, and pastiche. Examples of intertextuality in TV and film include a Family Guy episode that parodies Star Wars and relies on viewers' familiarity with Star Wars, as well as references to previous films in the Jurassic World franchise. In music, Eminem's "Without Me" video features a costume parodying Robin from Batman to present himself as a heroic figure.
The sci-fi genre incorporates hypothetical and science-based themes into futuristic storylines that explore social and philosophical issues. Common elements include heroes and villains, advanced technology, unfamiliar settings like space or other planets, and narratives involving the destruction of Earth or development of new technologies and their consequences. Character types range from aliens and robots to scientists and mutants, while settings include Earth or alternative versions of it in the future or parallel universes.
This document provides an overview of various media language techniques used in advertising, including:
- Camera shots and angles like close-up, wide shot, and high/low angles
- Technical elements like focus, framing, lighting, and mise-en-scène
- Symbolic codes from images, colors, and other visual elements
- The use of language techniques like slogans, fonts, and word choice
The document uses examples and descriptions to explain how these different techniques can be analyzed and how they contribute to conveying meaning and shaping audience perceptions of brands.
An epic is a long narrative poem that recounts the deeds of a larger-than-life hero who embodies the values of their society. Epics often concern conflicts between good and evil and are written on a grand scale. There are two types of epics: folk epics which are oral traditions that change over time, and literary epics which are fixed written works. Epics feature heroes who undertake extraordinary journeys and battles while gods or supernatural beings may intervene. The hero embodies the highest ideals of their culture and achieves immortality through their legacy.
Prometheus and Epimetheus were tasked with creating man after the Titanomachy. Prometheus shaped man out of mud and Athena breathed life into him. However, Epimetheus had used all the good qualities, so Prometheus gave man fire. Zeus punished man by requiring sacrifices but Prometheus tricked him. In retaliation, Zeus took fire from man but Prometheus stole it back. Zeus then had Hephaestus craft Pandora as the first woman to take revenge. Pandora's curiosity led her to open a forbidden jar, releasing all evils upon mankind. As further punishment, Prometheus was chained to a rock where an eagle ate his liver daily until eventually freed.
Drama tells a story through dialogue and stage directions meant to be performed on stage or screen. It includes elements like characters, setting, plot, theme, costumes, makeup, scenery, props, sound effects, music, acting, speaking, and nonverbal expression. A playwright authors a play and a scriptwriter authors a script for movies or television. Drama provides a different experience than novels or short stories because it is meant to be performed and enacted rather than simply read.
The document outlines several common conventions of science fiction films including setting them in the future, outer space, or alternative versions of earth. It also discusses including narratives focused on new technologies, scientific principles, or political systems, as well as conflicts between good and evil. Symbolism through futuristic props and costumes is used to represent scientific advancements. Film techniques like close-ups of technologies and special effects are employed to emphasize science elements and make fictional worlds more realistic.
The document discusses various techniques of mise-en-scène in film including shot types, camera angles, lighting styles, color, composition and more. It provides examples from films like Psycho, The Good the Bad and the Ugly, and Girl with the Pearl Earring to illustrate different techniques and how they can shape the tone and meaning of a scene.
Film sound is carefully designed to achieve particular goals and shape the audience's experience. There are different types of sound in films including vocal sounds like dialogue and narration, environmental sounds like ambient noise and effects, and music. Sound can come from diegetic sources visible on screen or nondiegetic sources not visible. It serves many functions such as creating continuity, shaping the sense of space, guiding audience attention, creating expectations, adding characterization, and commenting on the film images.
This is my take on iconography which is for my A Level Media project and this looks at what can be included when it come to the sub genre Crime Thriller. It includes what props and symbols that the genre features.
J.P. Clark's play Song of a Goat is set in an Ijaw community in Nigeria where impotence is socially stigmatized. The protagonist Zifa is impotent, which causes strife in his marriage as his wife Ebiere is unable to conceive. She engages in an affair with Zifa's brother Tonye and becomes pregnant. When Zifa learns of the affair, he kills a goat in a ritual to legitimize the adultery but forces Tonye to break an earthenware pot, symbolizing the destruction of Ebiere's womb. Overcome with guilt, Tonye commits suicide, and Zifa drowns himself. The play examines themes of fertility
The document provides an analysis of the opening scene of the film "Ex Machina". It summarizes the plot, genres (drama, mystery, sci-fi, thriller), and then analyzes specific shots from the opening scene. These include a close-up of the main character reacting to an email, a medium shot of him being applauded by coworkers, a long shot establishing the setting of a house, and shots of the character entering the house where doors close automatically behind him. The analysis discusses how these shots set up elements of mystery, isolation, and possible danger through the use of camera angles, lighting, and character reactions.
A2 Media The Hunger Games Genre Narrative and RepresentationElle Sullivan
The Hunger Games is a film based on the first book in a trilogy. It tells the story of Katniss Everdeen, a 16-year-old girl from District 12 who is chosen to compete in the annual Hunger Games, a battle to the death where 24 tributes fight each other. The genre is science fiction/action drama, with elements of social realism. While Katniss takes on more masculine traits like hunting, she also shows some feminine traits like caring for her sister. The film offers a positive representation of a strong female lead, while also challenging some gender stereotypes.
My presentation on the codes and conventions of thriller films which includes what they have to be and whats in a thriller film that makes it a thriller
The town of Endora represents entrapment and lack of opportunity. The endless road symbolizes possibilities beyond the town. Gilbert's mother symbolizes his emotional imprisonment and dependence. The burning of Gilbert's house acts as a cleansing that allows Gilbert freedom. Camera shots are used to position the audience and enhance the symbolism of these key features.
The fantasy genre uses magic and imaginary elements rather than supernatural ones. It is believed to have evolved from science fiction and contains clear differences. Fantasy films target families, teenagers, and young adults. While animated films like Snow White contain fantasy elements, they are categorized as fairy tales, a subgenre of fantasy. Successful fantasy films are often in trilogy formats like Lord of the Rings. The two main fantasy subgenres are high fantasy and sword and sorcery.
The document discusses common stock characters, plots, locations, and props used in horror films. Some key stock characters mentioned include the protagonist, antagonist, final girl, and children who are often used to connect the supernatural to other characters. Common plots involve a family moving to a haunted house/location and the father going insane. Isolated locations like cabins in the woods and haunted houses are frequently used due to their ability to create fear. Weapons are a common prop that illustrate vulnerability and are used by both antagonists and protagonists.
Kun Zhou presents research on emotion modelling for speech generation. The document outlines three topics: (1) Seq2Seq emotion modelling to improve generalizability with limited training data, (2) Modelling emotion intensity and developing methods for its control, and (3) Mixed emotion modelling and synthesis to generate speech with combined emotions. The overall goal is to develop more expressive and controllable speech synthesis by teaching machines to better imitate human emotional speech.
VAW-GAN for disentanglement and recomposition of emotional elements in speechKunZhou18
- The document describes a framework for emotional voice conversion using VAW-GAN that can disentangle and recompose emotional elements in speech. It proposes using VAW-GAN with continuous wavelet transform to model prosody and decompose fundamental frequency into different time scales. Conditioning the decoder on fundamental frequency is shown to improve emotion conversion performance. Experiments demonstrate the effectiveness of the approach on an English emotional speech database.
Iranian cinema has changed rapidly after the Iranian New Wave, so its better to have some ideas on this topic which I have collected from various books, research papers and journals.
Media key terms revision slides shots angles movement compositionMissConnell
The document defines various camera shots including establishing shots, close-ups, and point-of-view shots. It also explains different camera angles such as low angles and high angles. Finally, it covers compositional techniques for filming including symmetry, the rule of thirds, and manipulating the depth of field through shallow or deep focus.
The early history of film editing developed from single unedited shots by the Lumiere Brothers to more advanced techniques pioneered by Georges Melies, Edwin Porter, and others. Porter made one of the first films to tell a story through editing in 1903 with "The Life of an American Fireman." Russian filmmakers like Lev Kuleshov and Sergei Eisenstein experimented with editing to manipulate emotions and ideas, influencing others. D.W. Griffith's 1915 film "The Birth of a Nation" was a landmark as the first feature-length film to utilize varied camera angles and editing. Advances continued with filmmakers like Murnau and devices like the Moviola, revolutionizing the art of film editing.
Intertextuality refers to how a text draws meaning from other texts through techniques like allusion, quotation, translation, and pastiche. Examples of intertextuality in TV and film include a Family Guy episode that parodies Star Wars and relies on viewers' familiarity with Star Wars, as well as references to previous films in the Jurassic World franchise. In music, Eminem's "Without Me" video features a costume parodying Robin from Batman to present himself as a heroic figure.
The sci-fi genre incorporates hypothetical and science-based themes into futuristic storylines that explore social and philosophical issues. Common elements include heroes and villains, advanced technology, unfamiliar settings like space or other planets, and narratives involving the destruction of Earth or development of new technologies and their consequences. Character types range from aliens and robots to scientists and mutants, while settings include Earth or alternative versions of it in the future or parallel universes.
This document provides an overview of various media language techniques used in advertising, including:
- Camera shots and angles like close-up, wide shot, and high/low angles
- Technical elements like focus, framing, lighting, and mise-en-scène
- Symbolic codes from images, colors, and other visual elements
- The use of language techniques like slogans, fonts, and word choice
The document uses examples and descriptions to explain how these different techniques can be analyzed and how they contribute to conveying meaning and shaping audience perceptions of brands.
An epic is a long narrative poem that recounts the deeds of a larger-than-life hero who embodies the values of their society. Epics often concern conflicts between good and evil and are written on a grand scale. There are two types of epics: folk epics which are oral traditions that change over time, and literary epics which are fixed written works. Epics feature heroes who undertake extraordinary journeys and battles while gods or supernatural beings may intervene. The hero embodies the highest ideals of their culture and achieves immortality through their legacy.
Prometheus and Epimetheus were tasked with creating man after the Titanomachy. Prometheus shaped man out of mud and Athena breathed life into him. However, Epimetheus had used all the good qualities, so Prometheus gave man fire. Zeus punished man by requiring sacrifices but Prometheus tricked him. In retaliation, Zeus took fire from man but Prometheus stole it back. Zeus then had Hephaestus craft Pandora as the first woman to take revenge. Pandora's curiosity led her to open a forbidden jar, releasing all evils upon mankind. As further punishment, Prometheus was chained to a rock where an eagle ate his liver daily until eventually freed.
Drama tells a story through dialogue and stage directions meant to be performed on stage or screen. It includes elements like characters, setting, plot, theme, costumes, makeup, scenery, props, sound effects, music, acting, speaking, and nonverbal expression. A playwright authors a play and a scriptwriter authors a script for movies or television. Drama provides a different experience than novels or short stories because it is meant to be performed and enacted rather than simply read.
The document outlines several common conventions of science fiction films including setting them in the future, outer space, or alternative versions of earth. It also discusses including narratives focused on new technologies, scientific principles, or political systems, as well as conflicts between good and evil. Symbolism through futuristic props and costumes is used to represent scientific advancements. Film techniques like close-ups of technologies and special effects are employed to emphasize science elements and make fictional worlds more realistic.
The document discusses various techniques of mise-en-scène in film including shot types, camera angles, lighting styles, color, composition and more. It provides examples from films like Psycho, The Good the Bad and the Ugly, and Girl with the Pearl Earring to illustrate different techniques and how they can shape the tone and meaning of a scene.
Film sound is carefully designed to achieve particular goals and shape the audience's experience. There are different types of sound in films including vocal sounds like dialogue and narration, environmental sounds like ambient noise and effects, and music. Sound can come from diegetic sources visible on screen or nondiegetic sources not visible. It serves many functions such as creating continuity, shaping the sense of space, guiding audience attention, creating expectations, adding characterization, and commenting on the film images.
This is my take on iconography which is for my A Level Media project and this looks at what can be included when it come to the sub genre Crime Thriller. It includes what props and symbols that the genre features.
J.P. Clark's play Song of a Goat is set in an Ijaw community in Nigeria where impotence is socially stigmatized. The protagonist Zifa is impotent, which causes strife in his marriage as his wife Ebiere is unable to conceive. She engages in an affair with Zifa's brother Tonye and becomes pregnant. When Zifa learns of the affair, he kills a goat in a ritual to legitimize the adultery but forces Tonye to break an earthenware pot, symbolizing the destruction of Ebiere's womb. Overcome with guilt, Tonye commits suicide, and Zifa drowns himself. The play examines themes of fertility
The document provides an analysis of the opening scene of the film "Ex Machina". It summarizes the plot, genres (drama, mystery, sci-fi, thriller), and then analyzes specific shots from the opening scene. These include a close-up of the main character reacting to an email, a medium shot of him being applauded by coworkers, a long shot establishing the setting of a house, and shots of the character entering the house where doors close automatically behind him. The analysis discusses how these shots set up elements of mystery, isolation, and possible danger through the use of camera angles, lighting, and character reactions.
A2 Media The Hunger Games Genre Narrative and RepresentationElle Sullivan
The Hunger Games is a film based on the first book in a trilogy. It tells the story of Katniss Everdeen, a 16-year-old girl from District 12 who is chosen to compete in the annual Hunger Games, a battle to the death where 24 tributes fight each other. The genre is science fiction/action drama, with elements of social realism. While Katniss takes on more masculine traits like hunting, she also shows some feminine traits like caring for her sister. The film offers a positive representation of a strong female lead, while also challenging some gender stereotypes.
My presentation on the codes and conventions of thriller films which includes what they have to be and whats in a thriller film that makes it a thriller
The town of Endora represents entrapment and lack of opportunity. The endless road symbolizes possibilities beyond the town. Gilbert's mother symbolizes his emotional imprisonment and dependence. The burning of Gilbert's house acts as a cleansing that allows Gilbert freedom. Camera shots are used to position the audience and enhance the symbolism of these key features.
The fantasy genre uses magic and imaginary elements rather than supernatural ones. It is believed to have evolved from science fiction and contains clear differences. Fantasy films target families, teenagers, and young adults. While animated films like Snow White contain fantasy elements, they are categorized as fairy tales, a subgenre of fantasy. Successful fantasy films are often in trilogy formats like Lord of the Rings. The two main fantasy subgenres are high fantasy and sword and sorcery.
The document discusses common stock characters, plots, locations, and props used in horror films. Some key stock characters mentioned include the protagonist, antagonist, final girl, and children who are often used to connect the supernatural to other characters. Common plots involve a family moving to a haunted house/location and the father going insane. Isolated locations like cabins in the woods and haunted houses are frequently used due to their ability to create fear. Weapons are a common prop that illustrate vulnerability and are used by both antagonists and protagonists.
Kun Zhou presents research on emotion modelling for speech generation. The document outlines three topics: (1) Seq2Seq emotion modelling to improve generalizability with limited training data, (2) Modelling emotion intensity and developing methods for its control, and (3) Mixed emotion modelling and synthesis to generate speech with combined emotions. The overall goal is to develop more expressive and controllable speech synthesis by teaching machines to better imitate human emotional speech.
VAW-GAN for disentanglement and recomposition of emotional elements in speechKunZhou18
- The document describes a framework for emotional voice conversion using VAW-GAN that can disentangle and recompose emotional elements in speech. It proposes using VAW-GAN with continuous wavelet transform to model prosody and decompose fundamental frequency into different time scales. Conditioning the decoder on fundamental frequency is shown to improve emotion conversion performance. Experiments demonstrate the effectiveness of the approach on an English emotional speech database.
This presentation on Opinion Mining is part of the ARCOMEM training curriculum. Feel free to roam around or contact us on Twitter via @arcomem to learn more about ARCOMEM training on archiving Social Media.
This is the presentation of our IEEE ICASSP 2021 paper "seen and unseen emotional style transfer for voice conversion with a new emotional speech dataset".
This document discusses non-intrusive methods for recognizing a driver's emotions using vision and acoustic sensing in an advanced driver assistance system. It describes how emotions can impact driver attentiveness and safety. Six primary emotions are identified: anger, disgust, fear, happiness, sadness, and surprise. Various techniques are discussed for extracting visual features from face images and acoustic features from speech to classify emotions, along with their advantages and limitations. Prior work on emotion recognition from speech using Hidden Markov Models, spectral features, and other approaches is also summarized.
The document proposes a dense optical flow-based approach to emotion recognition from videos. It extracts dense optical flow features from labeled training videos to train an SVM classifier. During testing, it determines facial movements from unlabeled videos using optical flow and classifies the emotion. It achieved 82-90% accuracy on a dataset of 372 videos across 6 people expressing 4 emotions. Future work includes combining classifiers focusing on different facial regions and testing robustness to distance and camera angle.
Jalt 2012...spreading it...vocab sig presentation event...flyer & program finalAndy Boon
This document announces a day-long event featuring presentations by experts on vocabulary acquisition for EFL learners. Sponsored by JALT West Tokyo Chapter, the Vocabulary SIG, and Oxford University Press, the event will include talks on using technology like Word Engine to boost vocabulary learning, creating vocabulary lists tailored to students' needs, utilizing pictures to teach vocabulary formatively, and selecting appropriate online tools. It provides details on location, registration, and contact information for attendees interested in the professional development opportunities around vocabulary instruction offered at this event.
This document contains personal and professional details about Huaiping Ming. It summarizes that he is a research engineer born in 1986 working in audio and speech signal processing at the Institute for Infocomm Research in Singapore. It lists his educational background, research interests, qualifications, experiences, publications, and honors.
Augmenting Speech-Language Rehabilitation with Brain Computer Interfaces: An ...HCI Lab
Presentation on Aug 7, 2015 in the 17th International Conference on Human-Computer Interaction #HCII2015 in Los Angeles, CA, USA. The paper was presented in the Universal Access in Human-Computer Interaction track in the "Novel technologies for speech, language, attention and child development" session which was chaired by Prof. Margherita Antona, Foundation for Research & Technology - Hellas (FORTH), Greece http://2015.hci.international/friday
The document discusses opinion mining and sentiment analysis. It describes how opinion mining uses natural language processing techniques on user input from internet sources to understand opinions. Sentiment analysis is used to extract emotions, subjects, and the impact of opinions. The key modules of an opinion mining and sentiment analysis system include opinion retrieval, sentiment classification, and summary generation. Sentiment classification applies a semi-supervised naive Bayes classifier using linguistic features to determine the polarity of opinions. While current systems can effectively analyze sentiments, challenges remain in handling ambiguity and analyzing opinions in different languages.
This document describes an approach to morphological inflection generation using hard monotonic attention. The approach learns alignments between characters in the source and target words using a stepping mechanism, allowing linear decoding time. Evaluation on several datasets shows the model achieves state-of-the-art results, with hard alignments being more linguistically sensible than soft attention. Previous approaches like vanilla sequence-to-sequence models were not resolution preserving.
Efficient named entity annotation through pre-emptingLeon Derczynski
Linguistic annotation is time-consuming and expensive. One common annotation task is to mark entities – such as names
of people, places and organisations – in text. In a document, many segments of text often contain no entities at all. We show that these segments are worth skipping, and demonstrate a technique for reducing the amount of entity-less text examined
by annotators, which we call “preempting”. This technique is evaluated in a crowdsourcing scenario, where it provides downstream performance improvements for the same size corpus.
BASIC ANALYSIS ON PROSODIC FEATURES IN EMOTIONAL SPEECHIJCSEA Journal
Speech is a rich source of information which gives not only about what a speaker says, but also about what the speaker’s attitude is toward the listener and toward the topic under discussion—as well as the speaker’s own current state of mind. Recently increasing attention has been directed to the study of the emotional content of speech signals, and hence, many systems have been proposed to identify the emotional content of a spoken utterance. The focus of this research work is to enhance man machine interface by focusing on user’s speech emotion. This paper gives the results of the basic analysis on prosodic features and also compares the prosodic features
of, various types and degrees of emotional expressions in Tamil speech based on the auditory impressions between the two genders of speakers as well as listeners. The speech samples consist of “neutral” speech as well as speech with three types of emotions (“anger”, “joy”, and “sadness”) of three degrees (“light”, “medium”, and “strong”). A listening test is also being conducted using 300 speech samples uttered by students at the ages of 19 -22 the ages of 19-22 years old. The features of prosodic parameters based on the emotional speech classified according to the auditory impressions of the subjects are analyzed. Analysis results suggest that prosodic features that identify their emotions and degrees are not only speakers’ gender dependent, but also listeners’ gender dependent.
Conversational transfer learning for emotion recognitionTakato Hayashi
1) The document proposes an approach called TL-ERC that uses transfer learning to improve emotion recognition in conversations. TL-ERC pre-trains a hierarchical dialogue model on multi-turn conversation data and transfers its parameters to an emotion classifier.
2) Experiments show that TL-ERC improves performance and robustness over randomly initialized models, especially with limited training data. TL-ERC also reaches optimal validation performance in fewer training epochs.
3) Comparisons indicate TL-ERC outperforms previous state-of-the-art models for emotion recognition and is better able to leverage pre-trained weights than training from scratch.
Masterclass: Natural Language Processing in Trading with Terry Benzschawel & ...QuantInsti
This webinar introduced natural language processing techniques used in financial markets. It described how word embedding methods like bag-of-words, TF-IDF, Word2Vec, and BERT convert text into digital representations. These representations are used to generate sentiment scores from news headlines that can predict stock and bond returns over short horizons. The webinar recommended Quantra's online course on natural language processing in trading for its blend of theory, practical applications, and programming exercises applying these techniques to predict corporate bond returns.
Fusion of Learned Multi-Modal Representations and Dense Trajectories for Emot...Esra Açar
This document describes a method for emotional analysis of videos using multi-modal representations and dense trajectories. The method learns mid-level audio, static visual, and motion representations which are fused to classify video segments into emotional categories. It is evaluated on music video clips from the DEAP dataset and is shown to outperform approaches using only low-level features or other published methods.
The document describes the Columbia-GWU system submitted to the 2016 TAC KBP BeSt Evaluation. It discusses several approaches used for different languages and genres, including:
1) A sentiment system based on identifying the target only, adapted for English, Chinese, and Spanish.
2) An English sentiment system based on relation extraction, treating sentiment as a relation between source and target.
3) English and Chinese belief systems that combine high-precision word tagging with a high-recall default system.
4) A Spanish belief system based on weighted random choice of tags.
The document provides details on the data, approaches, and results for each language-specific system.
El modelo de traducción de voz de extremo a extremo de alta calidad se basa en una gran escala de datos de entrenamiento de voz a texto,
que suele ser escaso o incluso no está disponible para algunos pares de idiomas de bajos recursos. Para superar esto, nos
proponer un método de aumento de datos del lado del objetivo para la traducción del habla en idiomas de bajos recursos. En particular,
primero generamos paráfrasis del lado objetivo a gran escala basadas en un modelo de generación de paráfrasis
que incorpora varias características de traducción automática estadística (SMT) y el uso común
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y se propuso la co-ocurrencia de pares de palabras y habla para seleccionar la fuente con la puntuación más alta
pares de paráfrasis de los candidatos. Resultados experimentales en inglés, árabe, alemán, letón, estonio,
La generación de paráfrasis eslovena y sueca muestra que el método propuesto logra resultados significativos.
y mejoras consistentes sobre varios modelos de referencia sólidos en conjuntos de datos PPDB (http://paraphrase.
org/). Para introducir los resultados de la generación de paráfrasis en la traducción de voz de bajo recurso,
proponen dos estrategias: recombinación de pares audio-texto y entrenamiento de referencias múltiples. Experimental
Los resultados muestran que los modelos de traducción de voz entrenados en nuevos conjuntos de datos de audio y texto que combinan
los resultados de la generación de paráfrasis conducen a mejoras sustanciales sobre las líneas de base, especialmente en
lenguas de escasos recursos.
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ISO/IEC 27001, ISO/IEC 42001, and GDPR: Best Practices for Implementation and...PECB
Denis is a dynamic and results-driven Chief Information Officer (CIO) with a distinguished career spanning information systems analysis and technical project management. With a proven track record of spearheading the design and delivery of cutting-edge Information Management solutions, he has consistently elevated business operations, streamlined reporting functions, and maximized process efficiency.
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A Visual Guide to 1 Samuel | A Tale of Two HeartsSteve Thomason
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Good morning! I am PhD candidate from ECE department supervised by Prof. Li Haizhou. I am going to present my work on emotional voice conversion with non-parallel data during my first two years.
First I will give an introduction to emotional voice conversion and the related work. Next I will talk about my PhD research on this topic during these two years.
As we known, speech conveys information through linguistic, which refers to what we speak, and para-linguistic, which refers to how we speak. Emotional state is a para-linguistic attribute that can even reshape the meaning and understanding of the utterance.
Emotional voice conversion is a technique which aims to change the emotional state of an utterance. In the meantime, we would like to preserve the linguistic content and the speaker identity. At run-time, for example, if give the system a happy utterance [Play demo], we can get a sad utterance with the same speaking content and the same speaker [Play demo].
We can use this technology for many applications, such as social robots and conversational agents. It makes the synthesized voice more emotional and closer to the human voice.
In emotional voice conversion, there are still many challenges. For example, how to train an emotional voice conversion framework only with nonparallel and limited data is a challenging topic. Besides, emotional prosody is also difficult to model. And it is still difficult for us to control the output emotion strength. The current frameworks are also lack of generalizability, which means if we test the framework with unseen emotion or unseen speakers, the performance may not be so good.
Here is the list of the publications during the first two years of my PhD study. They are all about emotional voice conversion. I have five conference papers published, and one journal paper submitted.
Next I will introduce the related work on this topic. Previous studies on emotional voice conversion follow the pattern “analysis-mapping”, as shown in this figure. During the training, imagine we have a source speech which is neutral [Demo], and a target speech which is angry [Demo]. we first extract the speech features from the source and target utterance. We mostly use the spectral features and fundamental frequency to study spectrum and prosody. Then we train a conversion model to learn a feature mapping between the source and target features. Therefore, how to learn a feature mapping function has been the main focus of emotional voice conversion.
According to the training data, EVC can be divided into two types:
If the source and target speech are paired, which means if only the emotion is different, we call it as parallel data. But in real life, such data is expensive and difficult to collect.
Therefore, our research has been focusing on how to find a feature mapping function with non-parallel data, which means we have a source speech which is neutral [Demo], but we don’t have a target speech with the same content. Instead, we have a target speech with different content [Demo]. And we try to only learn the difference of emotional style between source and target. Compared with parallel data, emotional voice conversion with non-parallel data is much more challenging but more suitable for real-life applications.
When it comes to the conversion, we have a feature mapping function that we learnt from the last training stage. We first extract the speech features from the source speech, and give these features to the feature mapping function as the input. Then we can get the converted features through the feature mapping. Next we need to reconstruct the speech waveform from the converted features. We call this step as “waveform generation”. The model we used for this step we call it as vocoder. The vocoder quality determines the quality of the output speech. But speech quality is not our focus, we more care about the emotional expression in the output speech. We want the output emotion is more intelligible and more similar with the target emotion. Therefore, our main focus is to train a good feature mapping. And the emotional expression of the speech mostly depends on the feature mapping function. If we want to get a better speech quality, all we need to do is just to train a better vocoder. Here are some speech samples generated by different vocoders.
1/ the first one is Reference audio [Demo];
2/ the second one is synthesized by Griffin-Lim [Demo];
3/ This one is WaveRNN [Demo];
4/ This one is Parallel WaveGAN [Demo];
From these demos, the vocoder quality determines the speech quality. But my research is focus on the emotional expression rather than the speech quality.
In speech community, speaker voice conversion is a popular and well-studied research topic. Speaker voice conversion aims to convert the speaker identity and protect other prosodic attributes. Compared with speaker voice conversion, emotional voice conversion can be a more challenging task.
On the one hand, emotion is much more subjective and difficult to describe. And emotional style also complex with multiple signal attributes. Prosody, such as intonation, speaking rate, and speech energy, all play an important role in emotional expression and perception.
During the first two years, I propose and develop these four different frameworks on this topic. They all aim to tackle the current challenges we talked about in the previous slide. For these four frameworks, we always focus on finding nonparallel and limited data solutions for emotional voice conversion.
The first work I talk about is cycle-gan based evc, which is published in Speaker odyssey 2020. In this work, we aim to focus on non-parallel training and F0 modelling. F0, which is fundamental frequency, is an essential part of the intonation, varying from syllables to utterances which makes it difficult to model. Therefore we propose to use continuous wavelet transform to model F0 over multiple time scales. And convert it together with spectral features with CycleGAN. Moreover, we also investigate different training strategies to get a better performance.
We use continuous wavelet transform to study F0 modelling in different time scales. As shown in this figure, we decompose the F0 into ten scales, and we assume the lower scales can capture the short-term variations, such as syllables and phonemes, and higher scales can capture the long-term variations, such as phrases and utterances.
During training, we have two pipelines: the first is spectral cyclegan, which is to learn the feature mapping of spectral features, and another one is prosody cyclegan, to learn the mapping of CWT- F0 features given by continuous wavelet transform.
During conversion, these two models convert the spectral and F0 features from source to target emotion types.
We further conduct two listening tests to assess the final performance. The first figure shows , with continuous wavelet transform, the emotion similarity is improved, From the 2nd figure, we shows that the separate training of spectral and prosodic features outperforms the joint training. Here you can listen to some samples, if we have a source speech which is neutral [demo], we can convert it to angry [demo], sad [demo], and surprise [demo].
The second work I am going to talk about is speaker-independent EVC, which we publish on Interspeech 2020.
As we known, emotional expression shares some common cues across individuals. For example, no matter who speaks with happy, the fundamental frequency usually have a higher mean and standard variance than sad. So in this work, we study the universal pattern of emotional expression across different speakers, thus we call it as speaker-independent emotional voice conversion.
In the technical part, we propose a VAW-GAN-based architecture to enable non-parallel training, and study prosody modelling with continuous wavelet transform and F0 conditioning for encoder training.
Our proposed framework is based on VAW-GAN. It is a conditional variational auto-encoder followed by a discriminator. Compared with VAE, VAW-GAN can generate more realistic features. We further use VAW-GAN to study how to disentangle the emotional elements from speech. As the model input, spectral features contains speaker information which related to the speaker identity, phonetic information which is linguistic, and the prosodic information. We propose to provide emotion ID and F0 to the decoder, and the encoder can learn to discard emotion-related information and the latent code can be emotion-independent.
Our framework also consists of two pipelines, one for prosody and one for spectrum. For prosody pipeline, the encoder learns emotion-independent representation from CWT-F0 features and the generator learns to reconstruct prosody features with one-hot emotion label. The discriminator learns to judge whether the reconstructed features real or not.
The spectrum pipeline is similar with the prosody one. The only difference is we condition the generator not only with the emotion ID, but also the F0 values.
In experiments, we would like to validate our idea of 1/ CWT analysis on prosody modelling; 2/ F0 conditioning for encoder training; and 3/ performance with seen and unseen speakers. These two XAB preference test show the effectiveness of our proposed framework.
Next, I am going to talk about our work which published in this year ICASSP, EVC for seen and unseen emotions.
Current emotional voice conversion frameworks represent each emotion with one-hot emotion label, but such representation only learn to remember a fixed set of emotions and may not be sufficient to describe different emotional styles. As we known, the emotional styles also can present subtle difference even with the same emotion category.
In this work, we propose a one-to-many emotional style transfer framework. We use a pre-trained Speech Emotion Recognition model to describe different emotional styles. Our framework can work with non-parallel data and transfer the emotional style for both seen and unseen emotions.
There are three stages in our proposed framework.
In the 1st stage, we train a SER model and use it to get deep emotional features for each utterances;
Then we train the VAW-GAN framework with deep emotional features; the decoder learns to reconstruct the spectral features from the latent representation from the encoder, F0 and deep emotional features;
In the last stage run-time conversion, if we give the framework the deep emotional features of either seen emotion or unseen emotion, the framework can reconstruct the speech features with the reference emotional style.
We further conduct two preference tests for speech quality and emotion similarity. Both of them validate the effectiveness of our proposed framework.
The last work I am going to talk about is our recent work published in this year Interspeech, limited data EVC.
Previous work I talk about all convert the feature frame-by-frame, which means the speech duration always kept to be the same; but speech duration is an important factor in speech rhythm and it has been a missing point in these frame-based models.
To convert the speech duration, one solution is to train a sequence-to-sequence framework, which can predict the speech duration with the attention mechanism. But to train a seq2seq framework, we need a large amount of training data, nearly tens of hours to achieve a good prediction. If the training data is not sufficient, the framework may not learn a good alignment and the final performance will be poor. But for emotional speech data, there is no such large-scale datasets.
In this work, we are trying to build a seq2seq evc framework only requires a limited amount of emotional speech data, and can do both emotional voice conversion and emotional text-to-speech. Besides, it can jointly model spectrum, prosody, and duration; it can work with non-parallel training data and can do many-to-many conversion.
We propose a two-stage training for limited data evc: Style initialization and emotion training.
During style initialization, we leverage available large TTS corpus which is all neutral data. The style encoder learns speaker.
During the emotion training, we retrain the whole framework with limited amount of emotional speech data. The style encoder becomes an emotion encoder to learn the emotional style.
To validate our idea of two-stage training, we visualize the emotion embeddings derived from the style encoder and emotion encoder. From this figure, we observe that with emotion retraining, the emotion encoder can generate meaningful emotion representations and each emotion form separate clusters and there is a significant separation between different emotion types.
We choose two state-of-the-art emotional voice conversion frameworks CycleGAN and StarGAN for the baselines. We conduct emotion conversion from neutral to angry, happy, sad and surprise. Here are some speech samples. If we give a source neutral speech [demo], we can convert it to angry, it is cyclegan sounds like [demo], it is stargan[demo], it is our proposed [demo], it is the target[demo]. For the neutral to happy, it is the source[demo]….
From these speech samples, we can clearly feel that our proposed framework has a much better performance than the baselines, especially for the neutral-to-surprise.
Our framework also can do emotional text-to-speech. If we give an input text “clear than clear water” [demo], we can synthesis angry one[demo], sad[demo], surprise[demo], and happy[demo].
We further conduct listening experiments to evaluate the emotional expression. From this figure, we can observe that our framework significantly outperform the baselines in emotion similarity evaluation.
As a conclusion, in this presentation, we first introduce the emotional voice conversion and its theory and challenges. With these challenges, we introduce our work, which is CycleGAN based EVC, Speaker-independent EVC, EVC for seen and unseen emotions, and limited data EVC. For all the work, we provide the demo website and the codes are all available at github. As for future studies, we would like to these following topics, 1/ Emotional voice conversion with emotion strength control, which aims to control the output emotion strength, emotional interpolation for emotional voice conversion, which aims to convert the emotion in a continuous scale. Cross-lingual representations for emotional voice conversion, which aims to study a cross-lingual emotion representation across different languages.
It is the ending of this presentation. Thank you for listening!