Keywords:
- acoustic modeling
- Adaboost
- Alzheimer's disease
- Anti-spoofing
- articulatory features
- Artificial Neural Networks
- atypical speech
- Automatic accent assessment
- Automatic accent evaluation
- automatic gender recognition
- Automatic speaker verification (ASV)
- Automatic Speech Recognition
- automatic subword unit derivation
- bag of audio words
- Binary features
- binary masking
- BoAW
- boosting
- breathing pattern estimation
- breathing patterns
- Children speech recognition
- Classification
- CNN visualization
- ComParE features
- computational efficiency
- Conditional Random Fields
- confidence measures
- continuous speech recognition boosted binary features resource management
- Convolution Neural Network
- Convolutional neural network
- Convolutional Neural Networks
- COVID-19 identification
- cross-database
- deep learning
- deep neural networks
- depression detection
- Direction of arrival estimation
- dynamic programming
- Dysarthria
- Dysarthric speech
- embedding
- Emotion Recognition
- end-to-end acoustic modeling
- End-to-end learning
- end-to-end modelling
- end-to-end training
- expected performance and spoofability curve
- Expressive Vocalizations
- feature selection
- Few-shot learning
- fine-tuning
- fixed-size word patterns
- Formant identification
- Formants
- Fundamental frequency
- Fusion
- Gaussian mixture
- glottal source signals.
- grapheme
- Grapheme subword units
- grapheme subwords
- grapheme-to- phoneme conversion
- grapheme-to-phoneme conversion
- grapheme-to-phoneme converter
- Graphemes
- Hidden Markov Model
- hidden Markov models
- human skeleton estimation
- integration of ASV and anti-spoofing
- Inter-pretable Models
- isolated word recognition
- Kalman filters
- KL-divergence
- KL-HMM
- Kullback-Leibler divergence
- Kullback-Leibler divergence based hidden Markov model
- Kullback-Leibler divergence based HMM
- Kullback–Leibler divergence based hidden Markov model
- language disorder
- Language Production
- letter-to-sound rules
- lexical model
- Lexical modeling
- Lexicon
- local posterior probability
- localization
- long-term statistics
- low level descriptors
- Mental Lexicon
- microphone array
- microphone arrays
- mobile biometrics
- modalities fusion
- modified ZFF
- multi- layer perceptron
- Multi-modal Approach
- multi-stream combination
- Multi-task learning
- multilayer perceptron
- multilayer perceptron network
- multilingual acoustic modeling
- multiple linear regression
- Multiple speaker localization
- multiple speakers
- multiple-stream combination
- multitask learning
- neural network
- Noise Robustness
- non-native speech
- non-native speech recognition
- Objective Evaluation
- Objective intelligibility
- Objective intelligibility Assessment
- objective measures
- overlapping speech recognition
- Paralinguistic speech processing
- Parkinson's disease
- parts-based approach
- Pathological speech
- Pathological Speech Processing
- Perceived fluency
- phoneme
- phoneme modeling
- Phoneme recognition
- phoneme subword units
- phoneme subwords
- phonemes
- Phonetic information
- phonetic representation
- Phonocardiogram
- Posterior features
- posterior probabilities
- pre-trained embedding
- presentation attack
- Presentation Attack Detection
- probabilistic lexical modeling
- pronunciation generation
- pronunciation lexicon
- Raw Speech
- raw waveform modelling
- raw waveforms
- raw-waveform cnn
- Reading Assessment
- recognition
- recurrent neural network
- Respiratory parameters
- S1-S2 detection
- Scottish Gaelic
- segment-level training.
- Self-Organizing Maps
- Self-supervised embedding
- self-supervised learning
- sign language assessment
- Sign language processing
- signal processing
- sleepiness
- speaker verification
- speaker-specific features
- spectral statistics
- Speech Analysis
- speech assessment
- Speech breathing
- Speech Emotion Recognition
- Speech enhancement
- Speech intelligibility
- speech recognition
- speech recognition.
- speech separation
- speech synthesis
- Speech technology
- Spoofing
- spoofing detection
- Steered response power
- String matching
- SVM
- syllable-level-features
- synthetic reference templates.
- Synthetic speech
- TANDEM features
- template-based approach
- template-based system
- Text classification
- text-to-speech synthesis
- tracking
- under-resource speech recognition
- under-resourced languages
- universal phoneme set
- unsupervised adaptation
- utterance verification
- voice activity detection
- Voice Conversion
- zero frequency filter
- Zero frequency filtering
- zero-frequency filtering
- zero-resourced speech recognition
Publications of Mathew Magimai.-Doss sorted by title
A
| Approximating the Mental Lexicon from Clinical Interviews as a Support Tool for Depression Detection, , , , and , in: Proceedings of the 2021 International Conference on Multimodal Interaction, ACM, 2021 |
[DOI] |
| Articulatory Feature based Continuous Speech Recognition using Probabilistic Lexical Modeling, and , Idiap-RR-19-2014 |
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| Articulatory feature based continuous speech recognition using probabilistic lexical modeling, and , in: Computer Speech and Language, 36:233-259, 2016 |
[DOI] |
| Automatic Accentedness Evaluation of Non-Native Speech Using Phonetic and Sub-Phonetic Posterior Probabilities, , , and , Idiap-RR-12-2015 |
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| Automatic Accentedness Evaluation of Non-Native Speech Using Phonetic and Sub-Phonetic Posterior Probabilities, , , and , in: Proceedings of Interspeech, 2015 |
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| Automatic Speech Recognition using Pitch Information in Dynamic Bayesian Networks, , and , Idiap-RR-41-2000 |
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| Auxiliary Variables in Conditional Gaussian Mixtures for Automatic Speech Recognition, , and , in: Seventh International Conference on Spoken Language Processing (ICSLP~2002), 2002 |
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| Auxiliary Variables in Conditional Gaussian Mixtures for Automatic Speech Recognition, , and , Idiap-RR-25-2002 |
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B
| BOOSTED BINARY FEATURES FOR NOISE-ROBUST SPEAKER VERIFICATION, , and , in: 2010 IEEE International Conference on Acoustics, Speech and Signal Processing, Dallas, Texas, 2010 |
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| Boosting localized binary features for speech recognition, , and , in: Symposium on Machine Learning in Speech and Language Processing (MLSLP), 2012 |
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C
| Can Self-Supervised Neural Representations Pre-Trained on Human Speech distinguish Animal Callers?, and , in: Proceedings of Interspeech, 2023 |
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| Combination of Sparse Classification and Multilayer Perceptron for Noise Robust ASR, , , , , and , in: Proceedings of Interspeech, 2012 |
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| Combining Acoustic Data Driven G2P and Letter-to-Sound Rules for Under Resource Lexicon Generation, and , in: Proceedings of Interspeech, Portland, Oregon, 2012 |
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| Comparing Biosignal and Acoustic feature Representation for Continuous Emotion Recognition, , , , and , in: International Multimodal Sentiment Analysis Workshop and Challenge, 2022 |
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| COMPARING DATA-DRIVEN AND HANDCRAFTED FEATURES FOR DIMENSIONAL EMOTION RECOGNITION, , and , in: International Conference on Acoustics, Speech and Signal Processing, 2024 |
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| Comparing supervised and self-supervised embedding for ExVo Multi-Task learning track, , , and , in: Proceedings of the ICML Expressive Vocalizations Workshop held in conjunction with the 39th International Conference on Machine Learning, Maryland, USA, 2022 |
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| CONTENT-BASED OBJECTIVE EVALUATION OF ARTIFICIALLY GENERATED SIGN LANGUAGE VIDEOS, , , , , and , in: ICASSP, 2024 |
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| Continuous Speech Recognition using Boosted Binary Features, , and , Idiap-RR-35-2011 |
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| Convolutional Neural Networks-based Continuous Speech Recognition using Raw Speech Signal, , and , Idiap-RR-18-2014 |
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| Convolutional Neural Networks-based Continuous Speech Recognition using Raw Speech Signal, , and , in: International Conference on Acoustics, Speech and Signal Procecssing, IEEE, South Brisbane, QLD, pages 4295 - 4299, IEEE, 2015 |
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| Current trends in multilingual speech processing, , , , , , , , and , in: Sadhana, 36(5):885–915, 2011 |
[DOI] [URL] |
D
| Data-Driven Movement Subunit Extraction from Skeleton Information for Modeling Signs and Gestures, , and , Idiap-RR-02-2019 |
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| Deep learning architectures for estimating breathing signal and respiratory parameters from speech recordings, , , , and , in: Neural Networks, 141:211--224, 2021 |
[DOI] |
| Denoising and Raw-waveform Networks for Weakly-Supervised Gender Identification on Noisy Speech, , , , , and , in: Proceedings of Interspeech 2018, Hyderabad, INDIA, pages 292-296, 2018 |
[DOI] |
| Detection of S1 and S2 locations in phonocardiogram signals using zero frequency filter, , , and , in: Proceedings of the IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), 2020 |
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| Domain Adaptation and Investigation of Robustness of DNN-based Embeddings for Text-Independent Speaker Verification Using Dilated Residual Networks, , and , Idiap-RR-10-2019 |
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| Dynamic Bayesian Network Based Speech Recognition with Pitch and Energy as Auxiliary Variables, , , and , in: 2002 IEEE International Workshop on Neural Networks for for Signal Processing (NNSP~2002), 2002 |
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| Dynamic Bayesian Network Based Speech Recognition with Pitch and Energy as Auxiliary Variables, , , and , Idiap-RR-24-2002 |
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| Dysarthric Speech Recognition with Lattice-Free MMI, and , in: International Conference on Acoustics, Speech, and Signal Processing (ICASSP), pages 6109-6113, 2020 |
[DOI] [URL] |
E
| End-to-End Acoustic Modeling using Convolutional Neural Networks for Automatic Speech Recognition, , and , Idiap-RR-18-2016 |
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| End-to-End Acoustic Modeling using Convolutional Neural Networks for HMM-based Automatic Speech Recognition, , and , in: Speech Communication, 108:15--32, 2019 |
[DOI] |
| End-to-End Convolutional Neural Network-based Voice Presentation Attack Detection, , and , in: International Joint Conference on Biometrics, Denver, Colorado, USA, 2017 |
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| End-to-end Phoneme Sequence Recognition using Convolutional Neural Networks, , and , Idiap-RR-40-2013 |
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| Estimating Phoneme Class Conditional Probabilities from Raw Speech Signal using Convolutional Neural Networks, , and , Idiap-RR-13-2013 |
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| Estimating Phoneme Class Conditional Probabilities from Raw Speech Signal using Convolutional Neural Networks, , and , in: Proceedings of Interspeech, 2013 |
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| Estimating The Degree of Sleepiness by Integrating Articulatory Feature Knowledge In Raw Waveform Based CNNs, , and , Idiap-RR-06-2020 |
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| Estimating The Degree of Sleepiness by Integrating Articulatory Feature Knowledge In Raw Waveform Based CNNs, , and , in: International Conference on Acoustics, Speech, and Signal Processing (ICASSP), Barcelona, Spain, 2020 |
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| Evaluating the Robustness of Privacy-Sensitive Audio Features for Speech Detection in Personal Audio Log Scenarios, , , and , Idiap-RR-01-2010 |
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| Evaluating the Robustness of Privacy-Sensitive Audio Features for Speech Detection in Personal Audio Log Scenarios, , , and , in: ICASSP 2010, 2010 |
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| Exploiting Contextual Information for Improved Phoneme Recognition, , , and , in: "IEEE Int. Conf. on Acoustics, Speech, and Signal Processing (ICASSP)", 2008 |
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| Exploiting Contextual Information for Improved Phoneme Recognition, , , and , Idiap-RR-65-2007 |
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F
| Fast and flexible Kullback-Leibler divergence based acoustic modeling for non-native speech recognition, , and , Idiap-RR-01-2012 |
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