61–70 of 90 posts
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I was thinking earlier that maybe YouTube CC-licensed audio with manually entered subtitles might be a good source? Though, most videos of decent length would only contain say three or four speakers, which is most definitely sub-optimal. https://www.youtube.com/results?sp=EgYYAigBMAE%253D&search_q...
The last time I checked Youtube's terms of service prohibit you from making use of the rights granted by the creative commons licenses on the content.
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They have an iOS app too: https://itunes.apple.com/us/app/project-common-voice-by-mozi... It’s a great idea to crowd source this. Wonder if this project can turn voice recognition into a solved problem. I just set a daily reminder so I can do 10 minutes a day.
Thank you so much! I also want to emphasize the importance of listening (validating) as well as recording. Validation is an big part of the puzzle for building machine learning viable data.
And should we validate whether they match the proper accents as well? e.g. if I hear a clear Dutch accent, I presume you wouldn't want that labelled "native British speaker"?
This is super cool, but I'd be cautious about the usefulness of this data set. Both this data set and LibriSpeech are read speech, where the speaker was prompted with a transcription and asked to say it out loud. In practice it's very rare that you're trying to transcribe speech that's already been transcribed. Speech patterns for computer-directed speech (e.g. for voice activated user interfaces) or human-to-human s…
Yup, this is an excellent point. We have, and will continue to explore ways to allow Common Voice users to speak more organically (for instance by answering a question, or responding free-form to some other sort of prompt). The problem with this approach is that it requires an extra step, transcription, which at the scale we are trying to achieve is pretty costly in either money or time (ie. tedium for our users). Ev…
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Yup, this is an excellent point. We have, and will continue to explore ways to allow Common Voice users to speak more organically (for instance by answering a question, or responding free-form to some other sort of prompt). The problem with this approach is that it requires an extra step, transcription, which at the scale we are trying to achieve is pretty costly in either money or time (ie. tedium for our users). Ev…
Just had an idea... what about call center providers? They already collect speech data for training purposes and transcription could most likely help there!
The bigger problem is, of course, that you need speech data with (fairly) accurate transcripts for training ASR systems. These typically don't exist for call center calls.
Does this foreshadow a day when Firefox starts spying on what I'm talking about?
This is super cool, but I'd be cautious about the usefulness of this data set. Both this data set and LibriSpeech are read speech, where the speaker was prompted with a transcription and asked to say it out loud. In practice it's very rare that you're trying to transcribe speech that's already been transcribed. Speech patterns for computer-directed speech (e.g. for voice activated user interfaces) or human-to-human s…
Yup, this is an excellent point. We have, and will continue to explore ways to allow Common Voice users to speak more organically (for instance by answering a question, or responding free-form to some other sort of prompt). The problem with this approach is that it requires an extra step, transcription, which at the scale we are trying to achieve is pretty costly in either money or time (ie. tedium for our users). Ev…
Earlier quoted context omitted.
Yup, this is an excellent point. We have, and will continue to explore ways to allow Common Voice users to speak more organically (for instance by answering a question, or responding free-form to some other sort of prompt). The problem with this approach is that it requires an extra step, transcription, which at the scale we are trying to achieve is pretty costly in either money or time (ie. tedium for our users). Ev…
A speech recognition researcher I knew spent some time at Eastern Washington university because they had a lot of transcribed Washington state proceedings, which was open access enough to go into his company’s speech corpus, I guess (I only found out because I mentioned my mom graduated from there). Anyways, these people turn over a lot of rocks to realize their huge corpuses (erm, corpi?).
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Just had an idea... what about call center providers? They already collect speech data for training purposes and transcription could most likely help there!
They do, but privacy is a major concern. The bigger problem is, of course, that you need speech data with (fairly) accurate transcripts for training ASR systems. These typically don't exist for call center calls.
This is very timely, as today I was thinking of caving in and getting an Echo Dot so I can control my smart home devices by voice. I would love an open-hardware microphone array that I could use with a Pi or something similar, to write my own Alexa. Not only would I love this, I would store all my commands and send them to Mozilla to help with their speech recognition models. I don't want to be the guy who wishes som…
Not affiliated in any way but have you seen the MATRIX Creator or MATRIX Voice? Both contain microphone arrays that can interface with a Raspberry Pi. I’d love to see one of these meshed together with this new Mozilla voice project for an open source Echo or Google Home. The only missing piece it seems at this point is NLP and all of the glue that converts commands to API calls.
This is tangential, but I wonder if something like this could be (mis)used to break captcha - by feeding in the disabled-friendly audio captcha and passing the results back to the captcha server. As voice recognition becomes more sophisticated I think captchas are going to have to evolve to kjeep up as well.
So today, failure to captcha is actually an indication that the other end is human.