Unsupervised Domain Adaptation by Adversarial Learning for Robust Speech Recognition
Table 1: Summary of SPEECON corpora.
['[EMPTY]', 'Italian', 'French']
SPEECON is a family of speech corpora purposed for the development of speech recognition in consumer devices. The corpora were recorded for many languages according to the common specifications what allows us to evaluate the propose method in case of language mismatch while other conditions are not altered in a significant way. We use Italian data set for all the experiments and French as adaptation data in the cross-lingual experiment. Each corpus contains recordings of read and spontaneous speech by 550 adult speakers. The recordings are made in four acoustic environments: office, entertainment, public place and car. Each recording is made with 4 microphones located on different distances from the speaker that are represented by 4 channels in SPEECON corpora: Channel 1 corresponds to a close distance headset microphone placed right in front of the speaker’s mouth; Channel 2 corresponds to a lavalier microphone placed below the chin of the speaker; Channel 3 corresponds to a middle distance microphone placed in 0.5–1.0 meters from the speaker; Channel 4 corresponds to a far distance omni-directional microphone in office and entertainment environments or middle distance otherwise. Transcriptions are converted to lower case and cleaned up from punctuation marks. Summary of the used corpora is given in Tab.