2021 IEEE International Conference on Acoustics, Speech and Signal Processing

6-11 June 2021 • Toronto, Ontario, Canada

Extracting Knowledge from Information

2021 IEEE International Conference on Acoustics, Speech and Signal Processing

6-11 June 2021 • Toronto, Ontario, Canada

Extracting Knowledge from Information
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Paper Detail

Paper IDSPE-47.5
Paper Title ANALYSIS OF X-VECTORS FOR LOW-RESOURCE SPEECH RECOGNITION
Authors Martin Karafiat, Karel Vesely, Jan "Honza" Cernocky, Brno University of Technology, Czechia; Jan Profant, Jiri Nytra, Miroslav Hlavacek, Tomas Pavlicek, Phonexia.s.r.o., Czechia
SessionSPE-47: Speech Recognition 17: Speech Adaptation and Normalization
LocationGather.Town
Session Time:Friday, 11 June, 11:30 - 12:15
Presentation Time:Friday, 11 June, 11:30 - 12:15
Presentation Poster
Topic Speech Processing: [SPE-ADAP] Speech Adaptation/Normalization
IEEE Xplore Open Preview  Click here to view in IEEE Xplore
Abstract The paper presents a study of usability of x-vectors for adaptation of automatic speech recognition (ASR) systems. X-vectors are Neural Network (NN)-based speaker embeddings recently proposed in speaker recognition (SR). They quickly replaced common i-vectors and became new state-of-the-art technique. Here, the same approach is adopted for ASR with the hope of similar outcome. All experiments were done ASR for the latest IARPA MATERIAL evaluation running on Pashto language. Over 1% absolute improvement was observed with x-vectors over traditional i-vectors, even when the x-vector extractor was not trained on target Pashto data.