Speech to text is an automatic speech recognition (ASR) system that consists primarily of statistical models which map continuous spoken utterances or speech waveforms to text in human language. The ASR system is put together from a language model, a pronunciation model (lexicon/dictionary), and an acoustic model. When the ASR system is consistently fed and trained with new speech data by multiple speakers it receives an extended vocabulary, and the accuracy of the ASRs transcript increases. Therefore, the more the ASR has used the better accuracy it receives. The accuracy levels are measured and set by the Word Error Rate (WER).
For an ASR model to be considered highly accurate, the WER correspondence needs to be less than 10%. Txtplays ASR model is considered being highly accurate and that's because we deliver an accuracy of 94%.
Speech-to-text and automatic speech recognition (ASR) enable audio content to be visually accessible for everyone by adding text. Adding speech-to-text and subtitles provides accessibility for hearing-impaired audiences who would otherwise be excluded from this content. Therefore, automatic speech recognition (ASR) has become a necessity to possess to make content accessible to everyone.
Making online video content available to everyone has become a new EU directive set by the European Disability Forum Guidelines and the Web Content Accessibility Guidelines (WCAG).
EU directive dates and legislation:
Speech to text is an automatic speech recognition (ASR) system that consists primarily of statistical models which map continuous spoken utterances or speech waveforms to text in human language. The ASR system is put together from a language model, a pronunciation model (lexicon/dictionary), and an acoustic model. When the ASR system is consistently fed and trained with new speech data by multiple speakers it receives an extended vocabulary, and the accuracy of the ASRs transcript increases. Therefore, the more the ASR has used the better accuracy it receives. The accuracy levels are measured and set by the Word Error Rate (WER).
For an ASR model to be considered highly accurate, the WER correspondence needs to be less than 10%. Txtplays ASR model is considered being highly accurate and that's because we deliver an accuracy of 94%.
Speech-to-text and automatic speech recognition (ASR) enable audio content to be visually accessible for everyone by adding text. Adding speech-to-text and subtitles provides accessibility for hearing-impaired audiences who would otherwise be excluded from this content. Therefore, automatic speech recognition (ASR) has become a necessity to possess to make content accessible to everyone.
Making online video content available to everyone has become a new EU directive set by the European Disability Forum Guidelines and the Web Content Accessibility Guidelines (WCAG).
EU directive dates and legislation: