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Language Modeling and English Speech Prediction System to aid People with Stuttering Disorder
- 1. Language Modeling and English Speech Prediction System to aid People with Stuttering Disorder Chandana T L, Pramti Kalwad, Shailja Pattanaik, G Ram Mohana Reddy National Institute of Technology Karnataka, Surathkal
- 2. Introduction • Speech is one of the most natural mode of communication for interpersonal interactions. • English language has a level of ambiguity in the semantics which could change the manner in which the sentences are interpreted. This makes speech prediction a challenging problem. • Speech Completion aims at predicting the next word based on the previous words told by the user. • Stuttering: Involuntary repetition of words that affects the flow of speech in any language. • This paper aims at detecting stutter and modeling the language to predict the next word using the N-gram model of Natural Language Processing.
- 6. Next Word Prediction We generate unigrams, bigrams and trigrams from the corpus We generate trigrams by the following equation
- 7. Algorithm
- 8. Implementation • Corpus used: Our speech prediction based on the N-Gram language model utilizes ”Gutenberg” corpus from Natural Language Tool Kit available on Python. • The proposed system utilizes Google Speech to Text conversion API through a python library called pygsr 0.1. Google Speech to text conversion is an open source API which is used is used for voice search. • Python interface for the usage of this API is provided by pygsr 0.1. Our system is based on python platform due to the presence of several helping libraries and its wide supportability. • Python interface to use this API is provided by pygsr 0.1.
- 9. Results
- 10. Conclusion and Future Work • The system caters to the needs of the user with an accuracy of 87% in predicting the next word. • Limitations: The system caters only to repetitive word stuttering and not to other types of stuttering. • The accuracy with which the system predicts the next word is highly dependant on the size of the corpus. • Future Work: The future work will focus on other types of stuttering apart from repetitive word stuttering, primarily on the stuttering that occurs during the pronunciation of the word.