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Rich Transcription Tasks

The SRI/ICSI/UW Project Team will advance the state-of-the-art in automatic Rich Transcription of speech by creating a collection of novel models, algorithms, and techniques.

Core automatic speech recognition (ASR): Our objectives in this task are to markedly reduce the error rate for the core recognition process.  We will use a multifaceted approach to improve all aspects of the recognition system, leveraging all levels of information in the speech signal. Particularly, we will focus on the components that are 'broken' or have received little attention so far.

Rapid Development of ASR in New Languages and Domains (Portability) :

Metadata Extraction and Modeling: Currently ASR output is impoverished. Too much information is missing. In this task we seek to introduce structural information, such as from a good human transcriber, augment this with higher-level information, and feed information back to the recognizer to improve ASR. Metadata topics include:

Evaluation: In this task, we will develop and maintain a state-of-the-art Rich Transcription evaluation systems, essential both for evaluating new ASR technologies developed under this program and for participating in the annual EARS evaluations.

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