537 citations · 1k across the 21 of their papers we have counts for
24 papers
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…
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…
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…
Context-based out-of-vocabulary word recovery for ASR systems in Indian languages
Arun Baby, Saranya Vinnaitherthan, Akhil Kerhalkar +3
Detecting and recovering out-of-vocabulary (OOV) words is always challenging for Automatic Speech Recognition (ASR) systems. Many existing methods focus on modeling OOV words by mo…
STARSS22: A dataset of spatial recordings of real scenes with spatiotemporal annotations of sound events
Archontis Politis, Kazuki Shimada, Parthasaarathy Sudarsanam +7
This report presents the Sony-TAu Realistic Spatial Soundscapes 2022 (STARS22) dataset for sound event localization and detection, comprised of spatial recordings of real scenes co…
Differentiable Tracking-Based Training of Deep Learning Sound Source Localizers
Sharath Adavanne, Archontis Politis, Tuomas Virtanen
Data-based and learning-based sound source localization (SSL) has shown promising results in challenging conditions, and is commonly set as a classification or a regression problem…
A Dataset of Dynamic Reverberant Sound Scenes with Directional Interferers for Sound Event Localization and Detection
Archontis Politis, Sharath Adavanne, Daniel Krause +3
This report presents the dataset and baseline of Task 3 of the DCASE2021 Challenge on Sound Event Localization and Detection (SELD). The dataset is based on emulation of real recor…
Non-native English lexicon creation for bilingual speech synthesis
Arun Baby, Pranav Jawale, Saranya Vinnaitherthan +3
Bilingual English speakers speak English as one of their languages. Their English is of a non-native kind, and their conversations are of a code-mixed fashion. The intelligibility…
Overview and Evaluation of Sound Event Localization and Detection in DCASE 2019
Archontis Politis, Annamaria Mesaros, Sharath Adavanne +2
Sound event localization and detection is a novel area of research that emerged from the combined interest of analyzing the acoustic scene in terms of the spatial and temporal acti…
A Dataset of Reverberant Spatial Sound Scenes with Moving Sources for Sound Event Localization and Detection
Archontis Politis, Sharath Adavanne, Tuomas Virtanen
This report presents the dataset and the evaluation setup of the Sound Event Localization & Detection (SELD) task for the DCASE 2020 Challenge. The SELD task refers to the problem…
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…
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…
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…
Sound Event Localization and Detection of Overlapping Sources Using Convolutional Recurrent Neural Networks
Sharath Adavanne, Archontis Politis, Joonas Nikunen +1
In this paper, we propose a convolutional recurrent neural network for joint sound event localization and detection (SELD) of multiple overlapping sound events in three-dimensional…
Multichannel Sound Event Detection Using 3D Convolutional Neural Networks for Learning Inter-channel Features
Sharath Adavanne, Archontis Politis, Tuomas Virtanen
In this paper, we propose a stacked convolutional and recurrent neural network (CRNN) with a 3D convolutional neural network (CNN) in the first layer for the multichannel sound eve…
Sound event detection using weakly labeled dataset with stacked convolutional and recurrent neural network
Sharath Adavanne, Tuomas Virtanen
This paper proposes a neural network architecture and training scheme to learn the start and end time of sound events (strong labels) in an audio recording given just the list of s…
A report on sound event detection with different binaural features
Sharath Adavanne, Tuomas Virtanen
In this paper, we compare the performance of using binaural audio features in place of single-channel features for sound event detection. Three different binaural features are stud…
Direction of arrival estimation for multiple sound sources using convolutional recurrent neural network
Sharath Adavanne, Archontis Politis, Tuomas Virtanen
This paper proposes a deep neural network for estimating the directions of arrival (DOA) of multiple sound sources. The proposed stacked convolutional and recurrent neural network…
Sound Event Detection in Multichannel Audio Using Spatial and Harmonic Features
Sharath Adavanne, Giambattista Parascandolo, Pasi Pertilä +2
In this paper, we propose the use of spatial and harmonic features in combination with long short term memory (LSTM) recurrent neural network (RNN) for automatic sound event detect…
Stacked Convolutional and Recurrent Neural Networks for Music Emotion Recognition
Miroslav Malik, Sharath Adavanne, Konstantinos Drossos +3
This paper studies the emotion recognition from musical tracks in the 2-dimensional valence-arousal (V-A) emotional space. We propose a method based on convolutional (CNN) and recu…
Sound Event Detection Using Spatial Features and Convolutional Recurrent Neural Network
Sharath Adavanne, Pasi Pertilä, Tuomas Virtanen
This paper proposes to use low-level spatial features extracted from multichannel audio for sound event detection. We extend the convolutional recurrent neural network to handle mo…
Stacked Convolutional and Recurrent Neural Networks for Bird Audio Detection
Sharath Adavanne, Konstantinos Drossos, Emre Çakır +1
This paper studies the detection of bird calls in audio segments using stacked convolutional and recurrent neural networks. Data augmentation by blocks mixing and domain adaptation…
Automated Audio Captioning with Recurrent Neural Networks
Konstantinos Drossos, Sharath Adavanne, Tuomas Virtanen
We present the first approach to automated audio captioning. We employ an encoder-decoder scheme with an alignment model in between. The input to the encoder is a sequence of log m…
Convolutional Recurrent Neural Networks for Bird Audio Detection
EmreÇakır, Sharath Adavanne, Giambattista Parascandolo +2
Bird sounds possess distinctive spectral structure which may exhibit small shifts in spectrum depending on the bird species and environmental conditions. In this paper, we propose…