The design and collection of COSINE, a multi-microphone in situ speech corpus recorded in noisy environments

摘要

We present an overview of the data collection and transcription efforts for the Conversational Speech In Noisy Environments (COSINE) corpus. The corpus is a set of multi-party conversations recorded in real world environments with background noise. It can be used to train noise-robust speech recognition systems or develop speech de-noising algorithms. We explain the motivation for creating such a corpus, and describe the resulting audio recordings and transcriptions that comprise the corpus. These high quality recordings were captured in situ on a custom wearable recording system, whose design and construction is also described. On separate synchronized audio channels, seven-channel audio is captured with a 4-channel far-field microphone array, along with a close-talking, a monophonic far-field, and a throat microphone. This corpus thus creates many possibilities for speech algorithm research.