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20172026
most citedSound Event Detection in Multichannel Audio Using Spatial and Harmonic Features

87 citations · 305 across the 16 of their papers we have counts for

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cs.SD2026

Responsible ASR: Overcoming Challenges of Foundational Models in Narrow-Band and Low-Resource Settings

Tejas Godambe, Nutan Choudhary, Sanket Shah +2

Telephony conversations worldwide are conducted over narrow-band channels and are often spontaneous and colloquial in nature. This paper evaluates the performance of widely used fo…

cs.SD2023

STARSS23: An Audio-Visual Dataset of Spatial Recordings of Real Scenes with Spatiotemporal Annotations of Sound Events

Kazuki Shimada, Archontis Politis, Parthasaarathy Sudarsanam +9

While direction of arrival (DOA) of sound events is generally estimated from multichannel audio data recorded in a microphone array, sound events usually derive from visually perce…

cs.SD2022

Improving Speech Prosody of Audiobook Text-to-Speech Synthesis with Acoustic and Textual Contexts

Detai Xin, Sharath Adavanne, Federico Ang +3

We present a multi-speaker Japanese audiobook text-to-speech (TTS) system that leverages multimodal context information of preceding acoustic context and bilateral textual context…

cs.SD20205 cited

An ASR Guided Speech Intelligibility Measure for TTS Model Selection

Arun Baby, Saranya Vinnaitherthan, Nagaraj Adiga +4

The perceptual quality of neural text-to-speech (TTS) is highly dependent on the choice of the model during training. Selecting the model using a training-objective metric such as…

cs.SD20193 cited

A multi-room reverberant dataset for sound event localization and detection

Sharath Adavanne, Archontis Politis, Tuomas Virtanen

This paper presents the sound event localization and detection (SELD) task setup for the DCASE 2019 challenge. The goal of the SELD task is to detect the temporal activities of a k…

cs.SD2019

Localization, Detection and Tracking of Multiple Moving Sound Sources with a Convolutional Recurrent Neural Network

Sharath Adavanne, Archontis Politis, Tuomas Virtanen

This paper investigates the joint localization, detection, and tracking of sound events using a convolutional recurrent neural network (CRNN). We use a CRNN previously proposed for…