Deploying an automatic speech recognition system with reasonable performance requires
expensive and time-consuming in-domain transcription. Previous work demonstrated that …

To rapidly port speech applications to new languages one of the most difficult tasks is the
initial collection of sufficient speech corpora. State-of-the-art automatic speech recognition …

Automatic speech recognition tools have potential for facilitating language documentation,
but in practice these tools remain little-used by linguists for a variety of reasons, such as that …

This study investigates the use of Amazon Mechanical Turk for the transcription of nonnative
speech. Multiple transcriptions were obtained from several distinct MTurk workers and were …

Transcription makes speech accessible to deaf and hard of hearing people. This conversion
of speech to text is still done manually by humans, despite high cost, because the quality of …

Generating accurate word-level transcripts of recorded speech for language documentation
is difficult and time-consuming, even for skilled speakers of the target language. Automatic …

We introduce a new method for human-machine collaborative speech transcription that is
significantly faster than existing transcription methods. In this approach, automatic audio …

Transcription is typically a long and expensive process. In the last year, crowdsourcing
through Amazon Mechanical Turk (MTurk) has emerged as a way to transcribe large …

This paper describes the technical and system building advances made in IBM's speech
recognition technology over the course of the Defense Advanced Research Projects Agency …

We describe a novel approach to collecting orthographically transcribed continuous speech
data through the use of an online educational game called Voice Scatter, in which players …