Synchronizing text and audio - time alignment

We have implemented automatic and language independent text to audio alignment. What is it all about? In short, you upload your audio and text and you get the subtitles. See the pictures below.

What is the time alignment? The alignment is a process attaching time stamps to a transcript or text according to the audio. Usually the text is without timing. A sentence, a paragraph, a page of text does not have any timing information. But when you have an audio attached to this text -- means the audio contains a speech -- you may want to add the timing information to the text. To know when a particular word was spoken in the audio. You can imagine the process as making subtitles (time aligned sentences) from your text and audio.

The good news is that alignment can be done automatically and in our case even language independently.

What is the difference to automatic speech transcription? Well, in case you have only audio and want to get text (transcript, verbatim), you have to use automatic speech transcription -- to convert audio into text. But there are cases when you already have the transcript. Some examples might be:

• You wrote a script for a lecture, talk, pitch, or news. You "read" the text and got a recording. Now you want to make subtitles. It is waste of time and money to transcribe your speech again. Use the aligner.
• You asked someone to have transcribed your audio and then you got only plain text.  But you found subtitles useful later. Just align the previous transcript to your audio using our aligner.
• Can also be useful for e-book to audio-book alignment. 

Here you just need to put your audio and text into SpokenData.com and you will get aligned text (like subtitles). Plus you can use our editor to edit the text, timings, etc. You can use our API.

The largest advantage of our approach is in its independence from the language. It should work reasonably well for any language.  

This technology has also some caveats. It expects that the speech in the audio and the text fully matches. Assuming that you have part of your speech untranscribed or some notes in the text not spoken in the audio, the technology does its best to align it. So in such cases there can appear time shifts near these regions.

Онлайн перевод устной речи в текст - теперь с поддержкой русского языка!

Мы добавили на наш сайт поддержку русского языка, и теперь Вы можете расшифровывать записи с речью на русском! Просто залогиньтесь на SpokenData, загрузите свою запись и получите автоматическую письменную расшифровку текста на записи совершенно бесплатно! Вы также можете указать путь к вашей записи с помощью ссылки на YouTube, Vimeo или любой другой онлайн хостинг. Наша программа скачивает данные и конвертирует аудио в текст за считанные минуты. Когда расшифровка закончена, Вы получите оповещение по электронной почте. После этого Вы можете вностить изменения в текст с помощью нашего онлайн-редактора.

Для разработчиков программного обеспечения мы предоставляем простой в употреблении API.

Вы все еще не зарегистрированы на SpokenData.com? Пройдите быструю регистрацию здесь и откройте для себя возможности расшифровки Ваших аудио меньше, чем за минуту!

Russian voice to text online service.

Hi,

We added support of a new language - Russian. So, you can process any of your recordings in Russian now. Just log on SpokenData, submit your data and get automatic text transcript for free in few minutes. Another option is to provide us with URL of YouTube, Vimeo or other on-line services where your data is. We download the data and convert them into text quickly. You are notified by email when the conversion of audio into text is done. You can also edit the transcript yourself in our web editor later.
If you are a developer, feel free to integrate our API. It's easy.

You do not have SpokenData.com account yet? Just register here and you can process your data in 1 minute!

American Spanish speech to text for free!

Hello,

We are happy to announce that we support American Spanish now. So, if you have any voice recordings, you can process them in SpokenData to get automatic text transcript for free now. As our service is in cloud, it is very easy for you to get the text. Just take you audio or video files in Spanish and upload them.
The second option is to provide us with URL of YouTube, Vimeo or other on-line services. We download the data and convert them into text quickly. You are norified by email when the conversion is done. You can also edit the transcript yourself in our web editor later. If you are a developer, feel free to integrate our API. It's easy.

You do not have SpokenData.com account yet? Just register here and you can process your data in 1 minute!

Interactive waveform with Outwave.js

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.

Therefore, we are happy to announce that Outwave.js was integrated into the SpokenData subtitles editor. From now on, our users will more easily define speech or non-speech segments just by dragging the segment boundaries on the waveform with the mouse button held down.

We are certain you will benefit from the Outwave library as we do. The fastest way to test our new feature is to start the SpokenData demo and edit any recording subtitles.

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.

New Czech recognizer online

We are happy to announce that our new Czech recognizer is online at spokendata.com. The novelty lies in the support of 16kHz audio data (so called wideband) and also in robustness for distant microphones.
In comparison to the previous Czech recognizer, which was aimed at telephone data (8kHz - so called narrowband), the new one achieves better accuracy for:

• Speech recorded with higher quality - 16kHz or more. Unless you capture a telephone call, you usually record the data up to 44kHz.
• Distant microphone recordings. A telephone call recording is usually labeled as a close-talk because the speaker's mouth is close to the microphone. The distant microphone is the opposite case. Here the speaker's mouth is far from the microphone. As an example it can be a voice recorder or a mobile phone lying on the table while recording a dialog.

Fell free to test the recognizer by uploading your data and enjoy the transcript.