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.
- Some people do not understand English very well. Reading subtitles can help them understand.
- 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.
- 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.
SpokenData users can now download processed recording video in mp4, audio in mp3 and recording subtitles in a variety of formats. The files are accessible through the download menu or SpokenData API.
As some of our users host their recordings on Vimeo, we now support processing of Vimeo files. Simply enter a Vimeo url into the Media File URL input box. 
SpokenData API has a new function that enables users to search in recording transcriptions. This means that you can quickly get a list of captions matching the search query with their start and end time, caption content and speaker identity. The search can be performed either in all user recordings or in a list of selected recordings.
In SpokenData subtitles editor, we changed the rule of displaying the speaker segmentation. From now on, it is hidden by default except for the recordings processed directly by the Speaker segmentation method. However, the speaker segmentation can quickly be shown by clicking on the checkbox Show speaker segmentation. Currently, SpokenData subtitles editor does not support editing the generated speaker identity. When it is implemented, we will consider changing this rule.
Outwave.js is a handy library that can render audio waveform in a web browser. Its development was also supported by SpokenData. Apart from that, this library has a great extension for displaying annotation segments directly on the waveform. The segments can be easily added, deleted, merged or split. By and large, we really needed such a library.
