This paper introduces the Voices Obscured In Complex Environmental Settings (VOICES) corpus, a freely available dataset under Creative Commons BY 4.0. This dataset will promote speech and signal processing research of speech recorded by far-field microphones in noisy room conditions. Publicly available speech corpora are mostly composed of isolated speech at close-range microphony. A typical approach to better represent realistic scenarios, is to convolve clean speech with noise and simulated room response for model training. Despite these efforts, model performance degrades when tested against uncurated speech in natural conditions. For this corpus, audio was recorded in furnished rooms with background noise played in conjunction with foreground speech selected from the Lib-riSpeech corpus. Multiple sessions were recorded in each room to accommodate for all foreground speech-background noise combinations. Audio was recorded using twelve microphones placed throughout the room, resulting in 120 hours of audio per microphone. This work is a multi-organizational effort led by SRI International and Lab41 with the intent to push forward state-of-the-art distant microphone approaches in signal processing and speech recognition.

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The speakers in the room (SITR) corpus is a collaboration between Lab41 and SRI International, designed to be a freely available data set for speech and acoustics research in noisy room conditions. The main focus of the corpus is on distant microphone collection in a series of four rooms of different sizes and configurations. There are both foreground speech and background adversarial sounds, played through high-quality speakers in each room to create multiple, realistic acoustic environments. The foreground speech is played from a randomly rotating speaker to emulate head motion. Foreground speech consists of files from LibriVox audio collections and the background distractor sounds will consist of babble, music, HVAC, TV/radio, dogs, vehicles, and weather sounds drawn from the MUSAN collection. Each room has multiple sessions to exhaustively cover the background foreground combinations, and the audio is collected with twelve different microphones (omnidirectional lavalier, studio cardioid, and piezoelectric) placed strategically around the room. The resulting data set was designed to enable acoustic research on event detection, background detection, source separation, speech enhancement, source distance, sound localization, as well as speech research on speaker recognition, speech activity detection, speech recognition, and language recognition.