Keywords:
- Acoustic reverberation sparsity models
- Ad hoc array calibration
- Ad-hoc microphone array
- Automatic prosodic event detection
- Automatic Speech Recognition
- automatic speech recognition (ASR)
- Autoregressive modeling
- Beamforming
- Binary pattern matching
- cognition
- Compressive Acoustic Measurements
- Compressive sampling
- Compressive Sensing
- continuous F0 coding
- Convex optimization
- Convolutive source separation
- Deep neural network
- Deep neural network (DNN)
- Deep neural network posterior features
- Deep neural network posterior probabilities
- deep neural networks
- Dictionary learning
- Diffuse sound field
- Distant speech recognition
- Distributed source localization.
- Euclidean distance matrix
- exemplar-based modeling
- far-field asr
- Fast $k$NN
- Generalized cross correlation
- Generalized Trust Region Subproblem (GTRS).
- hidden variable
- Image Model
- Joint sparse recovery
- k-nearest neighbor (kNN) search
- Keyword Detection
- kNN classifier
- Least square solution.
- Linguistic parsing
- Low bit rate speech vocoding
- low-rank representation (LRR)
- low-rank sparsity
- Matrix completion
- microphone array
- Microphone array calibration
- missing data
- Model-Based Compressive Sensing
- Model-based sparse component analysis
- Model-based sparse recovery
- models
- Multi-party Speech
- Multi-party Speech Recognition
- Multi-speaker Localization
- nearest neighbour rule of classification.
- Non-negative matrix factorization
- Over-determined linear equation
- Overlapping Speech
- Pairwise distance estimation
- Phase transform
- Phone posterior
- Phoneme classification
- Phonological features
- Phonological posterior
- phonological posteriors
- posterior feature
- Posterior feature space
- Posterior hashing
- posterior probability
- Posterior probability structures
- Posterior representatives
- posterior space properties
- posterior-based metrics
- Pronunciation dewarping
- Quantized posterior hashing
- query by example
- Reverberant enclosure
- Reverberation
- Robust microphone placement
- Room acoustic characterization
- Room acoustic estimation
- Room Geometry
- Room geometry estima- tion
- Single-channel source localization
- skew- symmetric matrices
- soft targets
- Source localization
- sparse coding
- Sparse Component Analysis
- Sparse modeling
- Sparse Recovery
- sparse representation
- Sparse Signal Recovery
- Sparse word posterior probabilities
- Speaker localization
- speaker verification
- Spectrographic sparsity models
- Speech
- speech coding
- Speech dereverberation
- speech perception
- speech production
- speech recognition
- Speech source localization
- speech sparsity
- Speech spectral structures
- spiking neural networks
- spoken term detection
- Structural similarity measure
- Structured Sparse Coding
- Structured sparse representation
- Structured sparsity
- structured sparsity models
- Subspace detection
- synchronisation
- TDOA denoising
- TDOA estimation
- un- derdetermined convolutive speech separation
- Very low bit rate speech coding
- word emphasis
Publications of Afsaneh Asaei sorted by recency
| On quantifying the quality of acoustic models in hybrid DNN-HMM ASR, , and , in: Speech Communication, 119:24-35, 2020 |
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| Phonetic Subspace Features for Improved Query by Example Spoken Term Detection, , and , in: Speech Communication, 103:27-36, 2018 |
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| Far-field ASR Using Low-rank and Sparse Soft Targets from Parallel Data, , and , in: IEEE Workshop on Spoken Language Technology, Athens, GREECE, pages 581-587, IEEE, 2018 |
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| Phonological Posterior Hashing for Query by Example Spoken Term Detection, , and , in: Proceedings of Interspeech, 2018 |
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| Sparse Subspace Modeling for Query by Example Spoken Term Detection, , and , in: IEEE/ACM Transactions on Audio, Speech, and Language Processing, 2018 |
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| Cognitive Speech Coding: Examining the Impact of Cognitive Speech Processing on Speech Compression, , and , in: IEEE Signal Processing Magazine, 35(3):97-109, 2018 |
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| Perceptual Information Loss due to Impaired Speech Production, , and , in: IEEE/ACM Transactions on Audio, Speech, and Language Processing, 2017 |
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| Perceptual Information Loss due to Impaired Speech Production, , and , Idiap-RR-20-2017 |
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| Exploiting Eigenposteriors for Semi-supervised Training of DNN Acoustic Models with Sequence Discrimination, , and , in: Proceedings of Interspeech, 2017 |
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| Subspace Regularized Dynamic Time Warping for Spoken Query Detection, , and , in: Workshop on Signal Processing with Adaptive Sparse Structured Representations (SPARS), 2017 |
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| Sparse Pronunciation Codes for Perceptual Phonetic Information Assessment, , , and , in: Workshop on Signal Processing with Adaptive Sparse Structured Representations (SPARS), 2017 |
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| Low-rank and Sparse Soft Targets to Learn Better DNN Acoustic Models, , and , in: Proceedings of 2017 IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP 2017), 2017 |
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| Redundant Hash Addressing for Large-Scale Query by Example Spoken Query Detection, , and , Idiap-RR-31-2016 |
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| Information Theoretic Analysis of Production-Perception Efficiency: Case Study of Speech Pathology, , and , Idiap-RR-30-2016 |
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| Cognitive speech coding, and , Idiap-RR-27-2016 |
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| Composition of Deep and Spiking Neural Networks for Very Low Bit Rate Speech Coding, , , and , in: IEEE/ACM Trans. on Audio, Speech and Language Processing, 2016 |
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| Sparse Hidden Markov Models for Exemplar-based Speech Recognition Using Deep Neural Network Posterior Features, , and , Idiap-RR-19-2016 |
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| Efficient Posterior Exemplar Search Space Hashing Exploiting Class-Specific Sparsity Structures, , , and , in: Interspeech, San Francisco, CA, 2016 |
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| On Structured Sparsity of Phonological Posteriors for Linguistic Parsing, , and , in: Speech Communication, 84:36-45, 2016 |
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| PAoS Markers: Trajectory Analysis of Selective Phonological Posteriors for Assessment of Progressive Apraxia of Speech, , and , in: Proceeding on the 7th Workshop on Speech and Language Processing for Assistive Technologies (SLPAT), 2016 |
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| Low-Rank Representation of Nearest Neighbor Phone Posterior Probabilities to Enhance DNN Acoustic Modeling, , , and , in: Interspeech, 2016 |
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| Subspace Detection of DNN Posterior Probabilities via Sparse Representation for Query by Example Spoken Term Detection, , and , in: Interspeech, 2016 |
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| Sound Pattern Matching for Automatic Prosodic Event Detection, , , , and , in: Interspeech, San Francisco, USA, 2016 |
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| Exploiting Low-dimensional Structures to Enhance DNN based Acoustic Modeling in Speech Recognition, , , and , in: Proceedings of 2016 IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP 2016), Shanghai, pages 5690-5694, IEEE, 2016 |
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| Phonetic and Phonological Posterior Search Space Hashing Exploiting Class-Specific Sparsity Structures, , , and , Idiap-RR-10-2016 |
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| Composition of Deep and Spiking Neural Networks for Very Low Bit Rate Speech Coding, , , and , Idiap-RR-11-2016 |
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| On Structured Sparsity of Phonological Posteriors for Linguistic Parsing, , and , Idiap-RR-07-2016 |
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| Subspace Detection of DNN Posterior Probabilities via Sparse Representation for Query by Example Spoken Term Detection, , and , Idiap-RR-06-2016 |
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| Low-Rank Representation of Nearest Neighbor Phone Posterior Probabilities to Enhance DNN Acoustic Modeling, , , and , Idiap-RR-04-2016 |
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| Sound Pattern Matching for Automatic Prosodic Event Detection, , , , and , Idiap-RR-03-2016 |
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| Sparse Subspace Modeling for Query by Example Spoken Term Detection, , and , Idiap-RR-01-2016 |
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| On Compressibility of Neural Network phonological Features for Low Bit Rate Speech Coding, , and , in: Proceeding of Interspeech, pages 418-422, ISCA, 2015 |
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| TDOA Matrices: Algebraic Properties and their Application to Robust Denoising with Missing Data, , , and , in: IEEE Transactions on Signal Processing, 64(20):5242-5254, 2016 |
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| Binary Sparse Coding of Convolutive Mixtures for Sound Localization and Separation via Spatialization, , , , , and , in: IEEE Transactions on Signal Processing, 64(3):567-579, 2016 |
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| Spatial Sound Localization via Multipath Euclidean Distance Matrix Recovery, , , , and , in: IEEE Journal of Selected Topics in Signal Processing, 9(5):802-814, 2015 |
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