31 citations · 84 across the 13 of their papers we have counts for
13 papers
Vulnerability of Automatic Identity Recognition to Audio-Visual Deepfakes
Pavel Korshunov, Haolin Chen, Philip N. Garner +1
The task of deepfakes detection is far from being solved by speech or vision researchers. Several publicly available databases of fake synthetic video and speech were built to aid…
Can ChatGPT Detect Intent? Evaluating Large Language Models for Spoken Language Understanding
Mutian He, Philip N. Garner
Recently, large pretrained language models have demonstrated strong language understanding capabilities. This is particularly reflected in their zero-shot and in-context learning a…
The Interpreter Understands Your Meaning: End-to-end Spoken Language Understanding Aided by Speech Translation
Mutian He, Philip N. Garner
End-to-end spoken language understanding (SLU) remains elusive even with current large pretrained language models on text and speech, especially in multilingual cases. Machine tran…
An investigation into the adaptability of a diffusion-based TTS model
Haolin Chen, Philip N. Garner
Given the recent success of diffusion in producing natural-sounding synthetic speech, we investigate how diffusion can be used in speaker adaptive TTS. Taking cues from more tradit…
Surrogate Gradient Spiking Neural Networks as Encoders for Large Vocabulary Continuous Speech Recognition
Alexandre Bittar, Philip N. Garner
Compared to conventional artificial neurons that produce dense and real-valued responses, biologically-inspired spiking neurons transmit sparse and binary information, which can al…
Low-Level Physiological Implications of End-to-End Learning of Speech Recognition
Louise Coppieters de Gibson, Philip N. Garner
Current speech recognition architectures perform very well from the point of view of machine learning, hence user interaction. This suggests that they are emulating the human biolo…
Bayesian Recurrent Units and the Forward-Backward Algorithm
Alexandre Bittar, Philip N. Garner
Using Bayes's theorem, we derive a unit-wise recurrence as well as a backward recursion similar to the forward-backward algorithm. The resulting Bayesian recurrent units can be int…
A t-distribution based operator for enhancing out of distribution robustness of neural network classifiers
Niccolò Antonello, Philip N. Garner
Neural Network (NN) classifiers can assign extreme probabilities to samples that have not appeared during training (out-of-distribution samples) resulting in erroneous and unreliab…
A Bayesian Approach to Recurrence in Neural Networks
Philip N. Garner, Sibo Tong
We begin by reiterating that common neural network activation functions have simple Bayesian origins. In this spirit, we go on to show that Bayes's theorem also implies a simple re…
A Variational Prosody Model for Mapping the Context-Sensitive Variation of Functional Prosodic Prototypes
Branislav Gerazov, Gérard Bailly, Omar Mohammed +2
The quest for comprehensive generative models of intonation that link linguistic and paralinguistic functions to prosodic forms has been a longstanding challenge of speech communic…
Multilingual Training and Cross-lingual Adaptation on CTC-based Acoustic Model
Sibo Tong, Philip N. Garner, Hervé Bourlard
Multilingual models for Automatic Speech Recognition (ASR) are attractive as they have been shown to benefit from more training data, and better lend themselves to adaptation to un…
Composition of Deep and Spiking Neural Networks for Very Low Bit Rate Speech Coding
Milos Cernak, Alexandros Lazaridis, Afsaneh Asaei +1
Most current very low bit rate (VLBR) speech coding systems use hidden Markov model (HMM) based speech recognition/synthesis techniques. This allows transmission of information (su…
Ad Hoc Microphone Array Calibration: Euclidean Distance Matrix Completion Algorithm and Theoretical Guarantees
Mohammad J. Taghizadeh, Reza Parhizkar, Philip N. Garner +2
This paper addresses the problem of ad hoc microphone array calibration where only partial information about the distances between microphones is available. We construct a matrix c…