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Found 18 papers, 5 papers with code
Investigating Cross-lingual Multi-level Adaptive Networks: The Importance of the Correlation of Source and Target Languages
We experiment with three different scenarios using, i) French, as a source language uncorrelated to the target language, ii) Ukrainian, as a source language correlated to the target one and finally iii) English as a source language uncorrelated to the target language using a relatively large amount of data in respect to the other two scenarios.
Conversational Speech Recognition Needs Data? Experiments with Austrian German
Conversational speech represents one of the most complex of automatic speech recognition (ASR) tasks owing to the high inter-speaker variation in both pronunciation and conversational dynamics.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+2
Exploring neural oscillations during speech perception via surrogate gradient spiking neural networks
Understanding cognitive processes in the brain demands sophisticated models capable of replicating neural dynamics at large scales.
Bayesian Parameter-Efficient Fine-Tuning for Overcoming Catastrophic Forgetting
Our results demonstrate that catastrophic forgetting can be overcome by our methods without degrading the fine-tuning performance, and using the Kronecker factored approximations produces a better preservation of the pre-training knowledge than the diagonal ones.
Vulnerability of Automatic Identity Recognition to Audio-Visual Deepfakes
From the publicly available speech dataset LibriTTS, we also created a separate database of only audio deepfakes LibriTTS-DF using several latest text to speech methods: YourTTS, Adaspeech, and TorToiSe.
Can ChatGPT Detect Intent? Evaluating Large Language Models for Spoken Language Understanding
Recently, large pretrained language models have demonstrated strong language understanding capabilities.
The Interpreter Understands Your Meaning: End-to-end Spoken Language Understanding Aided by Speech Translation
Motivated particularly by the task of cross-lingual SLU, we demonstrate that the task of speech translation (ST) is a good means of pretraining speech models for end-to-end SLU on both intra- and cross-lingual scenarios.
An investigation into the adaptability of a diffusion-based TTS model
Given the recent success of diffusion in producing natural-sounding synthetic speech, we investigate how diffusion can be used in speaker adaptive TTS.
Surrogate Gradient Spiking Neural Networks as Encoders for Large Vocabulary Continuous Speech Recognition
Compared to conventional artificial neurons that produce dense and real-valued responses, biologically-inspired spiking neurons transmit sparse and binary information, which can also lead to energy-efficient implementations.
Low-Level Physiological Implications of End-to-End Learning of Speech Recognition
We investigate whether the inference can be inverted to provide insights into that biological system; in particular the hearing mechanism.
A surrogate gradient spiking baseline for speech command recognition
Artificial neural networks (ANNs) are the basis of recent advances in artificial intelligence (AI); they typically use real valued neuron responses.
Ranked #2 on
Audio Classification
on SSC
Bayesian Recurrent Units and the Forward-Backward Algorithm
Using Bayes's theorem, we derive a unit-wise recurrence as well as a backward recursion similar to the forward-backward algorithm.
A t-distribution based operator for enhancing out of distribution robustness of neural network classifiers
It is shown that classifiers that adopt this novel operator can be more robust to out of distribution samples, often outperforming NNs that use the standard softmax operator.
A Bayesian Approach to Recurrence in Neural Networks
We show that introduction of a context indicator leads to a variable feedback that is similar to the forget mechanism in conventional recurrent units.
A Variational Prosody Model for the decomposition and synthesis of speech prosody
Our work bridges between a comprehensive generative model of intonation and state-of-the-art AI techniques.
The SUMMA Platform Prototype
We present the first prototype of the SUMMA Platform: an integrated platform for multilingual media monitoring.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+5
Composition of Deep and Spiking Neural Networks for Very Low Bit Rate Speech Coding
Segmental errors are further propagated to optional suprasegmental (such as syllable) information coding.
Ad Hoc Microphone Array Calibration: Euclidean Distance Matrix Completion Algorithm and Theoretical Guarantees
This paper addresses the problem of ad hoc microphone array calibration where only partial information about the distances between microphones is available.
