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There are a lot of problems in speech besides transcription. I should have been clearer about what I meant. Even for people that do want transcription, though,
by praccu 11y ago
There are a lot of problems in speech besides transcription. I should have been clearer about what I meant.
Even for people that do want transcription, though, often you can handily beat the accuracy of off-the-shelf services by tuning the models to the domain.
I'm pasting some copy from our website in part because I can't talk too much about specifics, but here's some examples:
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High quality speech to text transcription, including in the very difficult areas of conversational human-to-human speech: phone calls, voicemails, meetings, etc.
Classification of speech & language: identifying gender, age, regional accents, level of education, etc.
Voice front-ends for various applications and devices, including natural language interfaces: heads-up displays, robots, smartphone apps, etc.
Speech synthesis (a.k.a. TTS) to generate high-quality synthesized speech from text.
Analysis of audio: detecting different types of noise or speech: dog bark, shouting, gunshot, water running, cars, etc.
Customization of speech recognition to processed signals, such as proprietary compression or noise reduction algorithms
Fine-grained analysis of speech and language, for giving feedback in language pathology or language learning.
Analysis of speech & language to detect various health conditions: stroke, dementia, depression, schizophrenia, etc.
Information extraction from text or audio: phone numbers, dates, entities and relationships, etc.
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[0] http://cobaltspeech.com/our-products.html http://cobaltspeech.com/our-products.html
- duaneb 11y agoSure, but best possible scenario you end up with a half-baked siri: interesting technology with gimmicky applications. Hardly a good use case to show case how ML can help a startup. The cost/benefit is huge for the general case using speech recognition.
- praccu 11y ago> 'There are a lot of problems in speech besides transcription. ' I'm trying to be vague because I don't want to violate NDAs and it's a pain to think up examples I'm not currently working on, but there are a lot of applications of machine learning to the _speech signal_ (rather than to the problem of speech to text; there are many other things you can predict) that are super interesting. Some examples are listed in the text I copied. > 'a half-baked siri' There are so many instances where speech-to-text is super useful for applications other than consumer facing CRUD apps. In a lot of varied industrial applications people are doing very cool things with speech; there are a lot of applications that need very targeted speech systems.
- duaneb 11y agoInteresting, sure. Useful or profitable is a separate point that needs a discrete argument. I'd argue it's still in the gimmick phase unless interface IS your product.