We can decode such mismatched transcripts using an information-theoretic decoder, resulting in a low-entropy probability distribution over the possible native- ...
Mismatched transcripts can be used to train ASR. Combining ten hours of mismatched transcripts with 12-48 minutes of native transcripts, if available, results ...
Abstract—Automatic speech recognition (ASR) converts audio to text. ASR is usually trained using a large quantity of labeled.
Mismatched transcripts can be used to train ASR, and if the authors don't even know the native phoneme inventory, mismatched transcripts in two or more ...
How to get it. , Mismatched crowdsourcing: Mining latent skills to acquire speech transcriptions. ; Asilomar Conference on Signals, Systems, and Computers ...
Mismatched crowdsourcing: Mining latent skills to acquire speech transcriptions. Conference Paper. Oct 2017. Mark Hasegawa-Johnson ...
Transcribed speech is a critical resource for building statistical speech recognition systems. Recent work has looked towards soliciting transcriptions for ...
Missing: Mining latent skills
Mismatched crowdsourcing: Mining latent skills to acquire speech transcriptions. Conference Paper. Oct 2017. Mark Hasegawa-Johnson ...
Mismatched crowdsourcing based language perception for under-resourced ... Mismatched crowdsourcing: Mining latent skills to acquire speech transcriptions.
Mark Hasegawa-Johnson | University of Illinois at Urbana ...
typeset.io › ... › Mark Hasegawa-Johnson
Mismatched crowdsourcing: Mining latent skills to acquire speech transcriptions · Dual-path Attention is All You Need for Audio-Visual Speech Extraction · Age ...