activity
20182026
most citedTime-Frequency Audio Features for Speech-Music Classification

4 citations · 5 across the 5 of their papers we have counts for

collaborators

5 papers

eess.AS2026

Evaluating Pretrained General-Purpose Audio Representations for Music Genre Classification

Kashish Rai, Mrinmoy Bhattacharjee

This study investigates the use of self-supervised learning embeddings, particularly BYOL-A, in conjunction with a deep neural network classifier for Music Genre Classification. Ou…

eess.AS2026

Timbre-Aware LLM-based Direct Speech-to-Speech Translation Extendable to Multiple Language Pairs

Lalaram Arya, Mrinmoy Bhattacharjee, Adarsh C. R. +1

Direct Speech-to-Speech Translation (S2ST) has gained increasing attention for its ability to translate speech from one language to another, while reducing error propagation and la…

eess.AS2025★ 1 cited

Fusion of Modulation Spectrogram and SSL with Multi-head Attention for Fake Speech Detection

Rishith Sadashiv T N, Abhishek Bedge, Saisha Suresh Bore +3

Fake speech detection systems have become a necessity to combat against speech deepfakes. Current systems exhibit poor generalizability on out-of-domain speech samples due to lack…

eess.AS2023

I-MSV 2022: Indic-Multilingual and Multi-sensor Speaker Verification Challenge

Jagabandhu Mishra, Mrinmoy Bhattacharjee, S. R. Mahadeva Prasanna

Speaker Verification (SV) is a task to verify the claimed identity of the claimant using his/her voice sample. Though there exists an ample amount of research in SV technologies, t…

eess.AS2018★ 4 cited

Time-Frequency Audio Features for Speech-Music Classification

Mrinmoy Bhattacharjee, S. R. M. Prasanna, Prithwijit Guha

Distinct striation patterns are observed in the spectrograms of speech and music. This motivated us to propose three novel time-frequency features for speech-music classification.…