#speech-synthesis

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#voice-cloning

HierSpeech++: All the Amazing Things It Could Do | HackerNoon

HierSpeech++ achieves high-quality zero-shot speech synthesis with a structured framework and improved inference speed, using minimal datasets.
The model shows potential for versatile applications, including voice cloning and emotion-controllable speech synthesis.

A Deeper Look at Speech Super-Resolution | HackerNoon

SpeechSR improves speech super-resolution by upsampling from 16 kHz to 48 kHz with superior performance and efficiency over existing models.

HierSpeech++: All the Amazing Things It Could Do | HackerNoon

HierSpeech++ achieves high-quality zero-shot speech synthesis with a structured framework and improved inference speed, using minimal datasets.
The model shows potential for versatile applications, including voice cloning and emotion-controllable speech synthesis.

A Deeper Look at Speech Super-Resolution | HackerNoon

SpeechSR improves speech super-resolution by upsampling from 16 kHz to 48 kHz with superior performance and efficiency over existing models.
morevoice-cloning
#zero-shot-learning

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.

Zero-shot Voice Conversion: Comparing HierSpeech++ to Other Basemodels | HackerNoon

HierSpeech++ demonstrates superior performance in voice style transfer compared to traditional models, significantly enhancing naturalness in speech synthesis.

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.

Zero-shot Voice Conversion: Comparing HierSpeech++ to Other Basemodels | HackerNoon

HierSpeech++ demonstrates superior performance in voice style transfer compared to traditional models, significantly enhancing naturalness in speech synthesis.
morezero-shot-learning
#voice-conversion

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 Limitations of HierSpeech++ and a Quick Fix | HackerNoon

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

Style Prompt Replication: A Simple Trick That Helped Us In Our Journey | HackerNoon

Style Prompt Replication (SPR) enables effective synthesis from short speech prompts, enhancing style transfer in speech generation.

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 Limitations of HierSpeech++ and a Quick Fix | HackerNoon

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

Style Prompt Replication: A Simple Trick That Helped Us In Our Journey | HackerNoon

Style Prompt Replication (SPR) enables effective synthesis from short speech prompts, enhancing style transfer in speech generation.
morevoice-conversion

Zero-shot Text-to-Speech With Prompts of 1s, 3s 5s, and 10s | HackerNoon

Zero-shot TTS performance improves with longer prompts; 1s prompts are insufficient for effective synthesis.

Is a Chat with a Bot a Conversation?

AI's advancement in speech synthesis raises questions about communication authenticity.

AI voice generators: What they can do and how they work

AI voice generation is becoming indistinguishable from human voices, posing both business opportunities and ethical concerns.
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