Gradient-based spectral visualization of CNNs using raw waveforms
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Decoding speech from intracranial recordings serves two main purposes: understanding the neural correlates of speech processing and decoding speech features for targeting speech neuroprosthetic devices. Intracranial recordings have high spatial and tempora ...
The prosody of the speech signal carries both linguistic and paralinguistic information. As such, there is a necessity of its modelling for the purpose of integrating it in speech technology systems. So far, there has been a multitude of proposed models fo ...
This work demonstrates an application of different real-time speech technologies, exploited in an online gaming scenario. The game developed for this purpose is inspired by the famous television based quiz-game show, “Who wants to be a millionaire”, in whi ...
We investigate a vocoder based on artificial neural networks using a phonological speech representation. Speech decomposition is based on the phonological encoders, realised as neural network classifiers, that are trained for a particular language. The spe ...
In this paper, we propose a platform based on phonological speech vocoding for examining relations between phonology and speech processing, and in broader terms, between the abstract and physical structures of speech signal. The goal of this paper is to go ...
Speaker diarization is the task of identifying “who spoke when” in an audio stream containing multiple speakers. This is an unsupervised task as there is no a priori information about the speakers. Diagnostical studies on state-of-the-art diarization syste ...
Deep neural networks (DNNs) have been recently introduced in speech synthesis. In this paper, an investigation on the importance of input features and training data on speaker dependent (SD) DNN-based speech synthesis is presented. Various aspects of the t ...
Assessment of speech intelligibility is important for the development of speech systems, such as telephony systems and text-to-speech (TTS) systems. Existing approaches to the automatic assessment of intelligibility in telephony typically compare a referen ...
Phonological features extracted by neural network have shown interesting potential for low bit rate speech vocoding. The span of phonological features is wider than the span of phonetic features, and thus fewer frames need to be transmitted. Moreover, the ...
We investigate a vocoder based on artificial neural networks using a phonological speech representation. Speech decomposition is based on the phonological encoders, realised as neural network classifiers, that are trained for a particular language. The spe ...