Fully managed and continuously trained automatic speech recognition service

Ashish Singh, Deepikaa Suresh, Vasanth Philomin, Rajkumar Gulabani, Vladimir Zhukov,Swaminathan Sivasubramanian,Vikram Sathyanarayana Anbazhagan, Praveen Kumar Akarapu,Stefano Stefani

user-5d4bc4a8530c70a9b361c870(2018)

Cited 2|Views23
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Abstract
Techniques for automated speech recognition (ASR) are described. A user can upload an audio file to a storage location. The user then provides the ASR service with a reference to the audio file. An ASR engine analyzes the audio file, using an acoustic model to divide the audio data into words, and a language model to identify the words spoken in the audio file. The acoustic model can be trained using audio sentence data, enabling the transcription service to accurately transcribe lengthy audio data. The results are punctuated and normalized, and the resulting transcript is returned to the user.
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Key words
Acoustic model,Transcription (software),Language model,Upload,Sentence,Speech recognition,Computer science
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