#voice-conversion

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#speech-synthesis

Conducting Ablation Studies to Verify the Effectiveness of Each Component in HierSpeech++ | HackerNoon

HierSpeech++ leverages advanced architecture improvements for enhanced zero-shot voice synthesis and voice conversion capabilities.

How We Used the LibriTTS Dataset to Train the Hierarchical Speech Synthesizer | HackerNoon

The paper discusses training a hierarchical speech synthesizer using the LibriTTS dataset, emphasizing the importance of data diversity for robust voice style transfer.

The 7 Objective Metrics We Conducted for the Reconstruction and Resynthesis Tasks | HackerNoon

The article explores advanced speech synthesis tasks using various metrics for evaluation, focusing on voice conversion and text-to-speech models.
It details the experimentation and methodologies applied in evaluating speech synthesis quality.

Zero-shot Text-to-Speech: How Does the Performance of HierSpeech++ Fare With Other Baselines? | HackerNoon

HierSpeech++ is a leading zero-shot text-to-speech model that excels in naturalness and overall performance.

HierSpeech++: How Does It Compare to Vall-E, Natural Speech 2, and StyleTTS2? | HackerNoon

The Hierspeech++ model outperforms existing models in naturalness and prompt similarity for zero-shot speech synthesis.
The evaluation revealed important limitations in similarity with ground truth versus prompt-generated speech.

The Limitations of HierSpeech++ and a Quick Fix | HackerNoon

The model enhances zero-shot speech synthesis but faces challenges with background noise and speech clarity.

Conducting Ablation Studies to Verify the Effectiveness of Each Component in HierSpeech++ | HackerNoon

HierSpeech++ leverages advanced architecture improvements for enhanced zero-shot voice synthesis and voice conversion capabilities.

How We Used the LibriTTS Dataset to Train the Hierarchical Speech Synthesizer | HackerNoon

The paper discusses training a hierarchical speech synthesizer using the LibriTTS dataset, emphasizing the importance of data diversity for robust voice style transfer.

The 7 Objective Metrics We Conducted for the Reconstruction and Resynthesis Tasks | HackerNoon

The article explores advanced speech synthesis tasks using various metrics for evaluation, focusing on voice conversion and text-to-speech models.
It details the experimentation and methodologies applied in evaluating speech synthesis quality.

Zero-shot Text-to-Speech: How Does the Performance of HierSpeech++ Fare With Other Baselines? | HackerNoon

HierSpeech++ is a leading zero-shot text-to-speech model that excels in naturalness and overall performance.

HierSpeech++: How Does It Compare to Vall-E, Natural Speech 2, and StyleTTS2? | HackerNoon

The Hierspeech++ model outperforms existing models in naturalness and prompt similarity for zero-shot speech synthesis.
The evaluation revealed important limitations in similarity with ground truth versus prompt-generated speech.

The Limitations of HierSpeech++ and a Quick Fix | HackerNoon

The model enhances zero-shot speech synthesis but faces challenges with background noise and speech clarity.
morespeech-synthesis

AI detection tools for audio deepfakes fall short. How 4 tools fare and what we can do instead - Poynter

AI-generated audio used in robocalls led to FCC ban
Challenges in detecting AI-generated audio clip
Deepfake audio is easier and cheaper to produce than video
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