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Found 19 papers, 9 papers with code
Sound Event Localization and Detection of Overlapping Sources Using Convolutional Recurrent Neural Networks
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 (3D) space.
Sound Audio and Speech Processing
Localization, Detection and Tracking of Multiple Moving Sound Sources with a Convolutional Recurrent Neural Network
This paper investigates the joint localization, detection, and tracking of sound events using a convolutional recurrent neural network (CRNN).
A multi-room reverberant dataset for sound event localization and detection
This paper presents the sound event localization and detection (SELD) task setup for the DCASE 2019 challenge.
Sound Audio and Speech Processing
A Dataset of Reverberant Spatial Sound Scenes with Moving Sources for Sound Event Localization and Detection
This report presents the dataset and the evaluation setup of the Sound Event Localization & Detection (SELD) task for the DCASE 2020 Challenge.
Overview and Evaluation of Sound Event Localization and Detection in DCASE 2019
A large-scale realistic dataset of spatialized sound events was generated for the challenge, to be used for training of learning-based approaches, and for evaluation of the submissions in an unlabeled subset.
STARSS22: A dataset of spatial recordings of real scenes with spatiotemporal annotations of sound events
Additionally, the report presents the baseline system that accompanies the dataset in the challenge with emphasis on the differences with the baseline of the previous iterations; namely, introduction of the multi-ACCDOA representation to handle multiple simultaneous occurences of events of the same class, and support for additional improved input features for the microphone array format.
Ranked #1 on
Sound Event Localization and Detection
on STARSS22
A Dataset of Dynamic Reverberant Sound Scenes with Directional Interferers for Sound Event Localization and Detection
This report presents the dataset and baseline of Task 3 of the DCASE2021 Challenge on Sound Event Localization and Detection (SELD).
Differentiable Tracking-Based Training of Deep Learning Sound Source Localizers
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.
STARSS23: An Audio-Visual Dataset of Spatial Recordings of Real Scenes with Spatiotemporal Annotations of Sound Events
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 perceptible source objects, e. g., sounds of footsteps come from the feet of a walker.
Multichannel Sound Event Detection Using 3D Convolutional Neural Networks for Learning Inter-channel Features
Each of this dataset has a four-channel first-order Ambisonic, binaural, and single-channel versions, on which the performance of SED using the proposed method are compared to study the potential of SED using multichannel audio.
Direction of arrival estimation for multiple sound sources using convolutional recurrent neural network
This paper proposes a deep neural network for estimating the directions of arrival (DOA) of multiple sound sources.
Automated Audio Captioning with Recurrent Neural Networks
The encoder is a multi-layered, bi-directional gated recurrent unit (GRU) and the decoder a multi-layered GRU with a classification layer connected to the last GRU of the decoder.
Sound Event Detection in Multichannel Audio Using Spatial and Harmonic Features
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 detection (SED) task.
Stacked Convolutional and Recurrent Neural Networks for Music Emotion Recognition
This paper studies the emotion recognition from musical tracks in the 2-dimensional valence-arousal (V-A) emotional space.
Sound Event Detection Using Spatial Features and Convolutional Recurrent Neural Network
This paper proposes to use low-level spatial features extracted from multichannel audio for sound event detection.
Stacked Convolutional and Recurrent Neural Networks for Bird Audio Detection
This paper studies the detection of bird calls in audio segments using stacked convolutional and recurrent neural networks.
Convolutional Recurrent Neural Networks for Bird Audio Detection
Bird sounds possess distinctive spectral structure which may exhibit small shifts in spectrum depending on the bird species and environmental conditions.
Non-native English lexicon creation for bilingual speech synthesis
Due to the inconsistency between the non-native English pronunciation in the audio and native English lexicon in the text, the intelligibility of synthesized speech in such TTS systems is significantly reduced.
Context-based out-of-vocabulary word recovery for ASR systems in Indian languages
We proposed two methods to determine a suitable cost function to retrieve the OOV words based on the context.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
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