Showing posts with label adaptation. Show all posts
Showing posts with label adaptation. Show all posts

Monday, July 14, 2014

Use case: How to transcribe conference video recordings and make subtitles for them?

One handy usage of automatic speech recognition technologies - speech-to-text - is a transcription of conference talks. There are plenty of conferences and lots of them are being recorded and published on a conference homepage or YouTube for example.
Let's use any conference as an example. To record the conference and to have plenty of videos on YouTube is fine, but it starts to be messy. You can find useful following reasons for transcribing talks.
  1. Some people do not understand English very well. Reading subtitles can help them understand.
  2. You need to market your conference to attract people. Videos show the quality of your conference to prospects. Transcribing the video to text increases your SEO. More people will find you.
  3. Large collections of videos can be searchable with a difficulty for particular information. Time synchronous speech transcript can help you search in speech quickly even in a large collection of videos.
To use human labor for subtitling videos make sense, because people do not like watching subtitles with errors - and automatic voice to text can make errors. On the other hand, transcribing all recordings from a several day long conference can be enormously expensive on human resources.
So the use of automatic voice to text technology is a logical step to reduce the need of human resources. Especially for cases 2) and 3). Here you do not care about a few errors, because the transcript is primarily for machines - search engines.

The huge advantage of our service here is the ability of automatic speech recognizer adaptation on the target domain - your conference. Usually, every technical conference has proceedings which are full of content words, abbreviations, technical terms etc. These words are important (within you conference) but rare in general speech. So standard recognizers trained on general speech can miss them easily and the transcript is useless for you.

To give you a real use case, SuperLectures - a conference video service - uses SpokenData.com automatic transcriptions in the above mentioned way. They provide us with proceedings so that we could adapt our recognizer. Then we return them textual transcription of their audio/video data.

Friday, January 24, 2014

Why do we need your speech data

Our several year experience in speech technology research and business shows often clash between:
Speech technology provider: "Give us some of your speech data for testing purposes please."
and
Customer: "No way! Our speech data is our private and secret property."

So let discuss several WHYs.

Why the speech technology provider wants the customer's data?

The speech technologies are very complex and sensitive to match between model and the data. This is common problem in the whole field of machine learning. Once you feed the classifier with "already seen" data, everything goes well. Accuracy of such algorithm is great.
The problem occurs when you put an unseen data into the algorithm - data which was not seen during training and developing. It is like, people living in US understands English because it is their already seen data, but does not understand Japanese because it is their unseen data during the training phase (childhood).