Monaural speech separation and recognition challenge

Robust speech recognition in everyday conditions requires the solution to a number of challenging problems, not least the ability to handle multiple sound sources. The specific case of speech recognition in the presence of a competing talker has been studied for several decades, resulting in a number of quite distinct algorithmic solutions whose focus ranges from modeling both target and competing speech to speech separation using auditory grouping principles. The purpose of the monaural speech separation and recognition challenge was to permit a large-scale comparison of techniques for the competing talker problem. The task was to identify keywords in sentences spoken by a target talker when mixed into a single channel with a background talker speaking similar sentences. Ten independent sets of results were contributed, alongside a baseline recognition system. Performance was evaluated using common training and test data and common metrics. Listeners' performance in the same tas...

• Type: Journal
• Year: 2010
• Where: CSL
• Authors: Martin Cooke, John R. Hershey, Steven J. Rennie
• Keywords: Automated Reasoning, CSL 2010, Robust Speech Recognition, Speech Recognition, Talker