State-of-the-art: Difference between revisions
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* Relevance: | * Relevance: | ||
==== APA Citation of | ==== APA Citation of NaturalSpeech: End-to-End Text to Speech Synthesis with Human-Level Quality ==== | ||
* Summary: | * '''Summary:''' NaturalSpeech proposes a system for converting text to speech (TTS) that achieves human-level quality. It leverages a variational autoencoder (VAE) to bridge the gap between text and speech waveforms. | ||
* RQ: | * '''RQ (Research Question):''' Can a TTS system achieve speech quality indistinguishable from humans? | ||
* Hypothesis: | * '''Hypothesis:''' By incorporating a VAE and specific techniques to improve the model's understanding of text and speech features, NaturalSpeech can generate speech indistinguishable from humans. | ||
* Conclusion: | * '''Conclusion:''' The paper argues that NaturalSpeech achieves human-level speech quality based on statistical measures (MOS and CMOS) in human evaluations. | ||
* Critical | * '''Critical Observations:''' The evaluation relies on subjective human ratings, which might be influenced by factors beyond speech quality.The research focuses on a single benchmark dataset, limiting generalizability.The paper doesn't explore how NaturalSpeech performs on diverse speaking styles or accents. | ||
* Relevance: | |||
* '''Relevance''': This is related to my study because it provides a definition of human-level quality, and this particular model has achieved the highest Mean Opinion Score (MOS) recorded thus far. Hence, I am considering using this model as a basis for my study. | |||
=== Synthesis === | === Synthesis === | ||
| Line 111: | Line 112: | ||
* Article Jones et al. 2023: YOUR NAME | * Article Jones et al. 2023: YOUR NAME | ||
* Article XXX: YOUR NAME | * Article XXX: YOUR NAME | ||
* Article NaturalSpeech: End-to-End Text to Speech Synthesis with Human-Level Quality: Yi Lei | |||
* Introduction: All | * Introduction: All | ||
* Synthesis: All | * Synthesis: All | ||
Revision as of 13:31, 20 March 2024
Theme: Template copy/paste but do not delete
Introduction
Briefly introduce your thematic focus and its significance in the field of speech technology.
Article summaries
- Article summaries and analyses: Each article receives a subsection including a summary (reference to RQ and hypothesis), critical analysis, and discuss its relevance to your theme.
APA Citation of an article
- Summary:
- RQ:
- Hypothesis:
- Conclusion:
- Critical observations:
- Relevance:
APA Citation of an article
- Summary:
- RQ:
- Hypothesis:
- Conclusion:
- Critical observations:
- Relevance:
Synthesis
Synthesis: Conclude with a section that synthesizes the key findings across the articles, highlighting any emerging trends, debates, or future research directions.
Contributors
Contributors: A list of contributors by contribution
- Article Jones et al. 2023: YOUR NAME
- Article XXX: YOUR NAME
- Introduction: All
- Synthesis: All
Language-specific Text-To-Speech
Introduction
Briefly introduce your thematic focus and its significance in the field of speech technology.
Article summaries
- Article summaries and analyses: Each article receives a subsection including a summary (reference to RQ and hypothesis), critical analysis, and discuss its relevance to your theme.
APA Citation of an article
- Summary:
- RQ:
- Hypothesis:
- Conclusion:
- Critical observations:
- Relevance:
APA Citation of an article
- Summary:
- RQ:
- Hypothesis:
- Conclusion:
- Critical observations:
- Relevance:
Synthesis
Synthesis: Conclude with a section that synthesizes the key findings across the articles, highlighting any emerging trends, debates, or future research directions.
Contributors
Contributors: A list of contributors by contribution
- Article Jones et al. 2023: YOUR NAME
- Article XXX: YOUR NAME
- Introduction: All
- Synthesis: All
Theme: Non-Language-specific Text-To-Speech
Introduction
Briefly introduce your thematic focus and its significance in the field of speech technology.
Article summaries
- Article summaries and analyses: Each article receives a subsection including a summary (reference to RQ and hypothesis), critical analysis, and discuss its relevance to your theme.
APA Citation of an article
- Summary:
- RQ:
- Hypothesis:
- Conclusion:
- Critical observations:
- Relevance:
APA Citation of NaturalSpeech: End-to-End Text to Speech Synthesis with Human-Level Quality
- Summary: NaturalSpeech proposes a system for converting text to speech (TTS) that achieves human-level quality. It leverages a variational autoencoder (VAE) to bridge the gap between text and speech waveforms.
- RQ (Research Question): Can a TTS system achieve speech quality indistinguishable from humans?
- Hypothesis: By incorporating a VAE and specific techniques to improve the model's understanding of text and speech features, NaturalSpeech can generate speech indistinguishable from humans.
- Conclusion: The paper argues that NaturalSpeech achieves human-level speech quality based on statistical measures (MOS and CMOS) in human evaluations.
- Critical Observations: The evaluation relies on subjective human ratings, which might be influenced by factors beyond speech quality.The research focuses on a single benchmark dataset, limiting generalizability.The paper doesn't explore how NaturalSpeech performs on diverse speaking styles or accents.
- Relevance: This is related to my study because it provides a definition of human-level quality, and this particular model has achieved the highest Mean Opinion Score (MOS) recorded thus far. Hence, I am considering using this model as a basis for my study.
Synthesis
Synthesis: Conclude with a section that synthesizes the key findings across the articles, highlighting any emerging trends, debates, or future research directions.
Contributors
Contributors: A list of contributors by contribution
- Article Jones et al. 2023: YOUR NAME
- Article XXX: YOUR NAME
- Article NaturalSpeech: End-to-End Text to Speech Synthesis with Human-Level Quality: Yi Lei
- Introduction: All
- Synthesis: All