In this paper, we develop Automatic Speech Recognition (ASR) systems for multi-genre speech recognition of low-resource languages where training data is predominantly conversational speech but test data can be in one of the following genres: news broadcast ...
In Bourlard and Kamp (Biol Cybern 59(4):291-294, 1998), it was theoretically proven that autoencoders (AE) with single hidden layer (previously called "auto-associative multilayer perceptrons") were, in the best case, implementing singular value decomposit ...
Altered quality of the phonetic-acoustic information in the speech signal in the case of motor speech disorders may reduce its intelligibility. Monitoring intelligibility is part of the standard clinical assessment of patients. It is also a valuable tool t ...
In this work, we propose lattice-free MMI (LFMMI) for supervised adaptation of self-supervised pretrained acoustic model. We pretrain a Transformer model on thousand hours of untranscribed Librispeech data followed by supervised adaptation with LFMMI on th ...
To assist the clinical diagnosis and treatment of speech dysarthria, automatic dysarthric speech detection techniques providing reliable and cost-effective assessment are indispensable. Based on clinical evidence on spectro-temporal distortions associated ...
IEEE Institute of Electrical and Electronics Engineers2021
In this work, we investigate if the wav2vec 2.0 self-supervised pretraining helps mitigate the overfitting issues with connectionist temporal classification (CTC) training to reduce its performance gap with flat-start lattice-free MMI (E2E-LFMMI) for autom ...
Starting from a strong Lattice-Free Maximum Mutual Information (LF-MMI) baseline system, we explore different autoencoder configurations to enhance Mel-Frequency Cepstral Coefficients (MFCC) features. Autoencoders are expected to generate new MFCC features ...
Automatic dysarthric speech detection can provide reliable and cost-effective computer-aided tools to assist the clinical diagnosis and management of dysarthria. In this paper we propose a novel automatic dysarthric speech detection approach based on analy ...
Automatic pathological speech intelligibility measures are crucial to assist the clinical diagnosis and treatment of speech disorders. The recently proposed pathological short-time objective intelligibility (P-ESTOI) measure was shown to be very advantageo ...
