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Impact of Naturalistic Field Acoustic Environments on Forensic Text-independent Speaker Verification System ...
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Speech variability: A cross-language study on acoustic variations of speaking versus untrained singing
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In: J Acoust Soc Am (2020)
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A speech perturbation strategy based on “Lombard effect” for enhanced intelligibility for cochlear implant listeners
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In: J Acoust Soc Am (2020)
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Leveraging native language information for improved accented speech recognition ...
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Quantifying Cochlear Implant Users’ Ability for Speaker Identification using CI Auditory Stimuli
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In: Interspeech (2019)
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Advancing Multi-Accented LSTM-CTC Speech Recognition using a Domain Specific Student-Teacher Learning Paradigm ...
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Abstract:
Non-native speech causes automatic speech recognition systems to degrade in performance. Past strategies to address this challenge have considered model adaptation, accent classification with a model selection, alternate pronunciation lexicon, etc. In this study, we consider a recurrent neural network (RNN) with connectionist temporal classification (CTC) cost function trained on multi-accent English data including US (Native), Indian and Hispanic accents. We exploit dark knowledge from a model trained with the multi-accent data to train student models under the guidance of both a teacher model and CTC cost of target transcription. We show that transferring knowledge from a single RNN-CTC trained model toward a student model, yields better performance than the stand-alone teacher model. Since the outputs of different trained CTC models are not necessarily aligned, it is not possible to simply use an ensemble of CTC teacher models. To address this problem, we train accent specific models under the guidance of ... : Accepted at SLT 2018 ...
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Keyword:
Audio and Speech Processing eess.AS; FOS Electrical engineering, electronic engineering, information engineering
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URL: https://dx.doi.org/10.48550/arxiv.1809.06833 https://arxiv.org/abs/1809.06833
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UTD-CRSS Submission for MGB-3 Arabic Dialect Identification: Front-end and Back-end Advancements on Broadcast Speech ...
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Robust Harmonic Features for Classification-Based Pitch Estimation
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The Lombard effect observed in speech produced by cochlear implant users in noisy environments: A naturalistic study
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KU-ISPL Language Recognition System for NIST 2015 i-Vector Machine Learning Challenge ...
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Multivariate cepstral feature compensation on band-limited data for robust speech recognition
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Evaluation and analysis of whispered speech for cochlear implant users: Gender identification and intelligibility
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Evaluation of the importance of time-frequency contributions to speech intelligibility in noise
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