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‘You talking to me?’ — Bringing MT to the world of chatbots
- 1. You talking to me? BringingMT to the world of chatbots Jose Palomares, CTO AMTA 2018
- 2. What is a chatbot Achatbot is a computer program designed to interact with users through a messaging (chat) service in a way that is designed to seem like a conversation. It provides a friendlier, more responsive way to interact with people by letting them communicate more naturally and without delays. In some cases, in addition to answering the chatbot’s questions, users can also ask the chatbot simple questions. NLP and AI are usually employed to achieve a genuine conversational UX. The application can be leveraged to both provide and gather data from users.
- 3. Support chatbots: Earlyprototypes
- 4. Chatbots’ reason to be UserExperience • Convenient access to relevant data in any situation • Messaging apps: Over 4 billion users • Alleviate frustration caused by traditional means and agents • Always on, no wait time (and easier to hang up on them!) Strategic Advantage • Reduced manual labor • Scalability and long-term savings • Avid data collection
- 5. A case for(multilingual) chatbots • 90% of businesses use Facebook to respond to service requests • Customers are 5 times more likely to message a company than posting on its Facebook page • The average messaging conversation is 66% longer than the average page conversation • 10 hours wait: Average time it takes for a company to respond to a message (about half if you post on their public wall) • 56% of businesses say engagement through messaging is ROI positive; 58% say it reduces costs Source: “Data: A Massive, Hidden Shift Is Driving Companies To Use A.I. Bots Inside Facebook Messenger,” BusinessInsider.com, May 12, 2016
- 8. Types of chatbots Flowtype • Diagram-driven (digital switchboard) • Highly specialized • Highly structured • Single data source 1 AI bots • Predictive • NLP + Machine Learning • (Big) Data-driven • Multiple data sources 2 Hybrids • Flow type + NLP • Human-assisted 3
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- 11. Chatbot design: Best practices •Keep communication simple • Short messages • Simple grammar • Don’t pretend to be a human • Avoid witty language • Sarcasm • Double meanings • Humor • If your first language is not good enough, don’t add any more yet
- 12. Content design for MT: Bestpractices • Keep communication simple • Short messages • Simple grammar • Don’t pretend to be a human • Avoid witty language • Sarcasm • Double meanings • Humor • If your first language is not good enough, don’t add any more yet
- 13. All the usualL10N challenges apply Ambiguity Context Gender Culture Lingo, humor, sarcasm Tone Intent Source quality
- 14. MT Opportunities: Multilingual AIbots • Help AI chatbot developers translate and refine data models • Intents • Entities • Phrase tables • Translate integrated data sources • Turn discarded utterances into data (intent, entities…) • Potential as continuous revenue stream
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- 16. MT opportunities: Flow typebots • Translate all entities and linked text/articles • Leverage existing enterprise language resources • Rapid implementation • Most interesting add-value service
- 17. MT opportunities: Hybrid models •Most common type • Error tolerance • Larger data sources • Knowledge bases • Product catalogs • Ticketing systems • Reward systems
- 18. MT opportunities: MT-assistedchatbot model
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- 20. Thank you! Jose Palomares CTO,Venga jose.palomares@vengaglobal.com linkedin.com/in/josepalomares/ @localizing