Sneha Das
Sneha Das
Postdoctoral researcher, Technical University of Denmark
Verified email at - Homepage
Cited by
Cited by
Postfiltering Using Log-Magnitude Spectrum for Speech and Audio Coding
S Das, T Bäckström
Interspeech 2018, 2018
Dithered Quantization for Frequency-Domain Speech and Audio Coding
T Bäckström, J Fischer, S Das
Interspeech 2018, 2018
Sound Privacy: A Conversational Speech Corpus for Quantifying the Experience of Privacy
PP Zarazaga, S Das, T Bäckström, VVV Raju, AK Vuppala
Interspeech 2019, 2019
Postfiltering with Complex Spectral Correlations for Speech and Audio Coding
S Das, T Bäckström
Interspeech 2018, 2018
Introduction to speech processing
T Bäckström, O Räsänen, A Zewoudie, P Perez Zarazaga, S Das
Towards Transferable Speech Emotion Representation: On loss functions for cross-lingual latent representations
S Das, NN Lønfeldt, AK Pagsberg, LH Clemmensen
ICASSP International Conference on Acoustics, Speech, and Signal Processing …, 2022
PyAWNeS-Codec: Speech and audio codec for ad-hoc acoustic wireless sensor networks
T Bäckström, MB Mansali, PP Zarazaga, M Ranjit, S Das, Z Lachiri
2021 29th European Signal Processing Conference (EUSIPCO), 1090-1094, 2021
Continuous Metric Learning For Transferable Speech Emotion Recognition and Embedding Across Low-resource Languages
S Das, NL Lund, NN Lønfeldt, AK Pagsberg, LH Clemmensen
Proceedings of the Northern Lights Deep Learning Workshop 3 (3), 2022
Speech Detection For Child-Clinician Conversations In Danish For Low-Resource In-The-Wild Conditions: A Case Study
S Das, NN Lønfeldt, AK Pagsberg, L Clemmensen
arXiv preprint arXiv:2204.11550, 2022
Enhancement by postfiltering for speech and audio coding in ad hoc sensor networks
S Das, T Bäckström
JASA Express Letters 1 (1), 015206, 2021
Perception of Privacy Measured in the Crowd−Paired Comparison on the Effect of Background Noises
A Leschanowsky, S Das, T Backstrom, PP Zarazaga
Interspeech 2020, 2020
Spectral Envelope Statistics for Source Modeling in Speech Enhancement
S Das, A Craciun, T Jaehnel, T Baeckstroem
12. ITG Symposium on Speech Communication, 1-5, 2016
Source Modelling Based on Higher-Order Statistics for Speech Enhancement Applications
S Das
Friedrich-Alexander-Universität Erlangen-Nürnberg, 2016
Computational behavior recognition in child and adolescent psychiatry: A statistical and machine learning analysis plan
NN Lønfeldt, FD Frumosu, ARC Mora-Jensen, NL Lund, S Das, ...
arXiv preprint arXiv:2205.05737, 2022
Zero-shot Cross-lingual Speech Emotion Recognition: A Study of Loss Functions and Feature Importance
S Das, NL Lund, NN Lønfeldt, AK Pagsberg, LH Clemmensen
2nd ISCA Symposium on Security and Privacy in Speech Communication, 23--29, 2022
Towards Interpretable and Transferable Speech Emotion Recognition: Latent Representation Based Analysis of Features, Methods and Corpora
S Das, NN Lønfeldt, AK Pagsberg, LH Clemmensen
arXiv preprint arXiv:2105.02055, 2021
Fundamental Frequency Model for Postfiltering at Low Bitrates in a Transform-Domain Speech and Audio Codec
S Das, T Backstrom, G Fuchs
Interspeech 2020, 2020
Low-Complexity Postfilter using MDCT-Domain for Speech and Audio Coding
S Das, T Bäckström
31st Conference on Electronic Processing of Speech Signals, 109--116, 2020
Privacy Analysis of Voice User Interfaces
F Yeasmin, S Das, T Bäckström
27th IEEE Conference of Open Innovations Association (FRUCT), 2020
Associations Between the Severity of Obsessive-Compulsive Disorder and Vocal Features in Children and Adolescents: Protocol for a Statistical and Machine Learning Analysis
LKH Clemmensen, NN Lønfeldt, S Das, NL Lund, VF Uhre, ...
JMIR Research Protocols 11 (10), e39613, 2022
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