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{
            
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  "access_rights": "",
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  "access_rights": "",
            
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  "author": "Yi Ren",
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  "author": "Yi Ren",
            
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  "author_email": "",
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  "author_email": "",
            
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  "citation": [],
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  "citation": [],
            
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  "defined_in": "",
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  "doi": "10.57702/jd8hw0cw",
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  "doi": "10.57702/jd8hw0cw",
            
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  "doi_date_published": null,
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  "doi_date_published": "2024-12-03",
            
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  "doi_publisher": "TIB",
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  "doi_publisher": "TIB",
            
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  "domain": "https://service.tib.eu/ldmservice",
            
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  "extra_authors": [
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  "extra_authors": [
            
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    {
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    {
            
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      "extra_author": "Zhejiang University",
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      "extra_author": "Zhejiang University",
            
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      "orcid": ""
            
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    },
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    {
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      "extra_author": "Yangjun Ruan",
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      "extra_author": "Yangjun Ruan",
            
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      "orcid": ""
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      "orcid": ""
            
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    },
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    {
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      "extra_author": "Zhejiang University",
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      "extra_author": "Zhejiang University",
            
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      "orcid": ""
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      "orcid": ""
            
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    },
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    },
            
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    {
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    {
            
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      "extra_author": "Xu Tan",
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      "extra_author": "Xu Tan",
            
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      "orcid": ""
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      "orcid": ""
            
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    },
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    },
            
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    {
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    {
            
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      "extra_author": "Microsoft Research",
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      "extra_author": "Microsoft Research",
            
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      "orcid": ""
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      "orcid": ""
            
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    },
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    },
            
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    {
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    {
            
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      "extra_author": "Tao Qin",
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      "extra_author": "Tao Qin",
            
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      "orcid": ""
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      "orcid": ""
            
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    },
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    },
            
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    {
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      "extra_author": "Microsoft Research",
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      "extra_author": "Microsoft Research",
            
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      "orcid": ""
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      "orcid": ""
            
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    },
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    },
            
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    {
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    {
            
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      "extra_author": "Sheng Zhao",
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      "extra_author": "Sheng Zhao",
            
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      "orcid": ""
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      "orcid": ""
            
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    },
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    },
            
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    {
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      "extra_author": "Microsoft STC Asia",
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      "extra_author": "Microsoft STC Asia",
            
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      "orcid": ""
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      "orcid": ""
            
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    },
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    },
            
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    {
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    {
            
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      "extra_author": "Zhou Zhao",
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      "extra_author": "Zhou Zhao",
            
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      "orcid": ""
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      "orcid": ""
            
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    },
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    },
            
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    {
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    {
            
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      "extra_author": "Zhejiang University",
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      "extra_author": "Zhejiang University",
            
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      "orcid": ""
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      "orcid": ""
            
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    },
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    },
            
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    {
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    {
            
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      "extra_author": "Tie-Yan Liu",
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      "extra_author": "Tie-Yan Liu",
            
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      "orcid": ""
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      "orcid": ""
            
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    },
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    },
            
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    {
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    {
            
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      "extra_author": "Microsoft Research",
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      "extra_author": "Microsoft Research",
            
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      "orcid": ""
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      "orcid": ""
            
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    }
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    }
            
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  ],
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  ],
            
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  "groups": [
            
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    {
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    {
            
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      "description": "",
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      "description": "",
            
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      "display_name": "Text-to-Speech",
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      "display_name": "Text-to-Speech",
            
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      "id": "486fb9b3-8453-4c88-bd0d-b9d59c07299c",
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      "image_display_url": "",
            
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      "name": "text-to-speech",
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      "name": "text-to-speech",
            
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      "title": "Text-to-Speech"
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      "title": "Text-to-Speech"
            
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    }
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    }
            
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  ],
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  ],
            
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  "id": "bb16220b-f154-4348-9b62-d42092c35995",
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  "id": "bb16220b-f154-4348-9b62-d42092c35995",
            
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  "isopen": false,
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  "isopen": false,
            
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  "landing_page": "https://speechresearch.github.io/fastspeech/",
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  "landing_page": "https://speechresearch.github.io/fastspeech/",
            
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  "license_title": null,
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  "license_title": null,
            
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  "link_orkg": "",
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  "link_orkg": "",
            
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  "metadata_created": "2024-12-03T10:00:40.083656",
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  "metadata_created": "2024-12-03T10:00:40.083656",
            
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  "metadata_modified": "2024-12-03T10:00:40.083661",
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  "metadata_modified": "2024-12-03T10:00:40.537720",
            
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  "name": "fastspeech--fast--robust-and-controllable-text-to-speech",
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  "name": "fastspeech--fast--robust-and-controllable-text-to-speech",
            
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  "notes": "Neural network based end-to-end text to speech (TTS) has 
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  "notes": "Neural network based end-to-end text to speech (TTS) has 
            
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signi\ufb01cantly improved the quality of synthesized speech. 
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signi\ufb01cantly improved the quality of synthesized speech. 
            
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Prominent methods (e.g., Tacotron 2) usually \ufb01rst generate 
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Prominent methods (e.g., Tacotron 2) usually \ufb01rst generate 
            
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mel-spectrogram from text, and then synthesize speech from the 
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mel-spectrogram from text, and then synthesize speech from the 
            
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mel-spectrogram using vocoder such as WaveNet. Compared with 
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mel-spectrogram using vocoder such as WaveNet. Compared with 
            
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traditional concatenative and statistical parametric approaches, 
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traditional concatenative and statistical parametric approaches, 
            
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neural network based end-to-end models suffer from slow inference 
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neural network based end-to-end models suffer from slow inference 
            
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speed, and the synthesized speech is usually not robust (i.e., some 
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speed, and the synthesized speech is usually not robust (i.e., some 
            
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words are skipped or repeated) and lack of con-trollability (voice 
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words are skipped or repeated) and lack of con-trollability (voice 
            
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speed or prosody control). In this work, we propose a novel 
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speed or prosody control). In this work, we propose a novel 
            
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feed-forward network based on Transformer to generate mel-spectrogram 
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feed-forward network based on Transformer to generate mel-spectrogram 
            
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in parallel for TTS.",
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in parallel for TTS.",
            
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      "display_name": "parallel mel-spectrogram generation",
            
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      "name": "parallel mel-spectrogram generation",
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      "name": "parallel mel-spectrogram generation",
            
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      "state": "active",
            
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    {
            
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      "display_name": "speech synthesis",
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      "display_name": "speech synthesis",
            
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      "id": "499bf7ec-2e42-4899-bdb2-55134754d900",
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      "id": "499bf7ec-2e42-4899-bdb2-55134754d900",
            
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      "name": "speech synthesis",
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      "name": "speech synthesis",
            
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      "state": "active",
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      "state": "active",
            
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      "vocabulary_id": null
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      "vocabulary_id": null
            
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    },
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    },
            
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    {
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    {
            
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      "display_name": "text to speech",
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      "display_name": "text to speech",
            
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      "id": "ac666b23-d181-4a43-95dd-66ac96d940e7",
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      "id": "ac666b23-d181-4a43-95dd-66ac96d940e7",
            
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      "name": "text to speech",
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      "name": "text to speech",
            
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      "state": "active",
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      "state": "active",
            
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      "vocabulary_id": null
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      "vocabulary_id": null
            
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    }
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    }
            
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  ],
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  ],
            
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  "title": "FastSpeech: Fast, Robust and Controllable Text to Speech",
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  "title": "FastSpeech: Fast, Robust and Controllable Text to Speech",
            
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  "type": "dataset",
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  "type": "dataset",
            
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  "version": ""
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  "version": ""
            
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}
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}