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The availability of smart devices leads to an exponential increase in multimedia content. However, advancements in deep learning have also enabled the creation of highly sophisticated deepfake content, including speech Deepfakes, which pose a serious ...

During the development of a speech synthesizer, we often face a lack of training data. This paper describes how the amount of data used to train a speech synthesizer affects the quality of the final synthetic speech. To answer this question, we ...

Although current Text-To-Speech (TTS) models are able to generate high-quality speech samples, there are still challenges in developing emotion intensity controllable TTS. Most existing TTS models achieve emotion intensity control by extracting ...

This paper discusses the integration of cutting-edge technologies, especially artificial intelligence (AI) and speech synthesis in UETL environment. By using methods based on artificial intelligence, such as Fuzzy Convolutional Neural Network (FCNN) and ...

The voice of widely used conversational agents (CAs) is standardized to be highly intelligible, yet it still sounds machine-generated due to its artificial qualities. With advancements in deep neural networks, voice synthesis technology has become ...

In the era of advanced text-to-speech (TTS) systems capable of generating high-fidelity, human-like speech by referring a reference speech, voice cloning (VC), or zero-shot TTS (ZS-TTS), stands out as an important subtask. A primary challenge in ...

This study presents the results of two perception experiments aimed at evaluating the effect that specific patterns of disfluencies have on people listening to synthetic speech. We consider the particular case of Cultural Heritage presentations ...

• Neural speech synthesis systems model speech phenomena in a natural-sounding way.
• Neural synthesis can work as a tool to investigate human speech behaviours.
• In specific contexts, speech disfluency phenomena foster listeners’ ...

Short-wave communication has unstable channel conditions, but it is still widely used in military and diplomatic fields due to its security, high destruction resistance and full coverage characteristics. Therefore, in order to adapt to transmission in ...

Representations of AI agents in user interfaces and robotics are predominantly White, not only in terms of facial and skin features, but also in the synthetic voices they use. In this paper we explore some unexpected challenges in the representation of ...

Voice conversion systems have become increasingly important as the use of voice technology grows. Deep learning techniques, specifically generative adversarial networks (GANs), have enabled significant progress in the creation of synthetic media, ...

• Top-K improves GAN-based voice conversion systems for better quality & naturalness.
• Top-K improves convergence & training stability of voice conversion systems.
• Effectiveness of Top-K is supported through quantitative and ...

With the advent of deep learning, Text-to-Speech technology has been revolutionized, and current state-of-the-art models are capable of synthesizing almost human-like speech. Recent Text-to-Speech models use a sequence-to-sequence architecture ...

Integrating natural language understanding, voice command interpretation and natural language generation for realtime inference is a challenging problem. However, developing a proof of concept is now possible in just a few lines of code which was ...

• Different metrics for spectral stability identification in vowels are discussed.
• A new metric is introduced.
• The different metrics are assessed both on synthesized and natural speech.
• Higher-dimensional metrics capture spectral ...

This study investigated the performance of several metrics used to evaluate spectral stability in vowels. Four metrics suggested in the literature and a newly developed one were tested and compared to the traditional method of associating the ...

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With the advent of automated speaker verification (ASV) systems comes an equal and opposite development: malicious actors may seek to use voice spoofing attacks to fool those same systems. Various counter measures have been proposed to detect ...

The prevalence of voice spoofing attacks in today’s digital world has become a critical security concern. Attackers employ various techniques, such as voice conversion (VC) and text-to-speech (TTS), to generate synthetic speech that imitates the victim’...

End-to-end (e2e) speech synthesis systems have become popular with the recent introduction of text-to-spectrogram conversion systems, such as Tacotron, that use encoder–decoder-based neural architectures. Even though those sequence-to-...

• Few-shot speaker adaptation using lightweight neural postfilters for text-to-speech.

The main concern behind deriving natural sounding synthesized speech lies in the objective mapping of the relation between formal and functional representations of prosody in human speech. Besides stress, rhythm, and duration, intonation is the ...

This paper presents an investigation of speaker adaptation using a continuous vocoder for parametric text-to-speech (TTS) synthesis. In purposes that demand low computational complexity, conventional vocoder-based statistical parametric speech ...

Text-to-speech systems (TTS) have come a long way in the last decade and are now a popular research topic for creating various human-computer interaction systems. Although, a range of speech synthesis models for various languages with several ...

Speech provides a natural way for human–computer interaction. In particular, speech synthesis systems are popular in different applications, such as personal assistants, GPS applications, screen readers and accessibility tools. However, not all ...