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1 Takuma Okamoto1, Yamato Ohtani1, Sota Shimizu2,1, Tomoki Toda3,1 and Hisashi Kawai1 1National Institute of Information and Communications Technology, Japan 2Kobe University, Japan 3Nagoya University, Japan ˏKos Island, Greece Challenge of Singing Voice Synthesis Using Only Text-To-Speech Corpus With FIRNet Source-Filter Neural Vocoder

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Introduction Conventional methods and problems Proposed method: Uni fi ed text-to-speech (TTS) and singing voice synthesis (SVS) framework Experiments Demo samples Conclusion Outline 2 Speech demo samples

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High- fi delity and fast neural TTS and SVS models TTS: Input text -> speaking speech waveform SVS: Input musical scores (lyrics and notes) -> singing speech waveform Actual applications Useful to perform SVS with the same speaker voice as TTS Problems SVS corpora are more expensive to collect than TTS corpora Introduction 3 Investigating SVS only using TTS data

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NICT developed neural TTS on smartphones 4 High- fi delity and fast 21-language neural TTS on smartphones Latencies: 0.5 on mid-range (Google Pixel 5) and 0.2 on high-range (Google Pixel 8) 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 waveform 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AAACcXichVHLLgRBFD3T3uM12BCbjgmRyEzujLeFEAk2BGOQeKW7FSp6ujvdPZMw8QN+gMSKRER8ho0fsPAJYjkSGwt3elrEArdSdW+duufeU1W6Y0rPJ3qOKFXVNbV19Q3RxqbmltZYW/uaZ+ddQ2QN27TdDV3zhCktkfWlb4oNxxVaTjfFun40Uz5fLwjXk7a16h87YjunHVhyXxqaz9DOQiYxO5OYl7MyMTe9uBuLU3KcxodGBlVKUmAcDFF6dGxQTYVIHKEt2bFbbGEPNgzkkYOABZ9jExo8HptIgeAwto0iYy5HMjgXOEWUuXnOEpyhMXrE6wHvNkPU4n25phewDe5i8nSZqaKXnuiOSvRI9/RCH7/WKgY1ylqO2esVrnB2W886M+//snLsfRx+s/7U7GMfY4FWydqdACnfwqjwCyfnpczESm+xj67plfVf0TM98A2swptxsyxWLhHlD/h6ZfX3YC2dTI0kh5fT8anJ8Cvq0Y0e9PN7j2IK81hClvu6uMAVriMlpUtRlZ5KqhIJOR34YcrAJz5EjiM= MS-FC-HiFi-GAN 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 Input text 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 (Mel-spectrogram) 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 Fast and high fidelity coustic model 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 Fast and high-fidelity 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 waveform generative model Show & Tell paper T. Okamoto, Y. Ohtani and H. Kawai, “Mobile PresenTra: NICT fast neural text-to-speech system on smartphones with incremental inference of MS-FC-HiFi-GAN for low-latency synthesis,” in Proc. Interspeech, Sept. 2024, pp. 997—998. (Show & Tell)

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High- fi delity and fast neural TTS and SVS models TTS: Input text -> speaking speech waveform SVS: Input musical scores (lyrics and notes) -> singing speech waveform Actual applications Useful to perform SVS with the same speaker voice as TTS Problem SVS corpora are more expensive to collect than TTS corpora Introduction 5 Realizing SVS only using TTS data

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Ranges of fundamental frequency and phoneme duration in SVS are wider than those in TTS JSUT: Single speaker TTS corpus for Japanese (Takamichi+ 2020) JVS-Song: SVS corpus for Japanese singed by the same speaker of JSUT Why challenging? 6 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 (a) Fundamental frequency 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 (b) Phoneme duration

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UniSyn: Uni fi ed end-to-end TTS and SVS model (Lei+ AAAI 2023) Trained from multi-speaker TTS and SVS corpus SVS can be performed for a speaker whose singing data are not included in the training set Collection of multi-speaker TTS and SVS corpora is costly. Melody unsupervised SVS model (Choi+ ICASSP 2022) SVS using only TTS data (Only demo samples) Only SVS can be performed but TTS cannot be performed Di ffi cult to extrapolate fundamental frequency
 outside the range of training data Fundamental frequency trajectory tends to be stair-stepped Previous methods and problems 7 LJSpeech can sing songs!!

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High- fi delity cascade neural TTS model Acoustic model: Conformer-Fastspeech 2 with monotonic alignment search Neural vocoder: HiFi-GAN conditioned on mel-spectrogram Baseline TTS model 8 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 Input text 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 Phoneme (+ accentual) sequence 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 Comformer-based decoder 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 Variance adapter 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 Comformer-based encoder 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 Embedding layer 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 Text analyzer 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 Predicted acoustic feature 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 CFS2-based acoustic model 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 Output speech waveform AAACdHichVHLSsNAFD2Nr1ofrboRdCGGihvLVFCLq4IbN4Ja+4BaShLHGpoXybSgxR/wB1x0pSgifoYbf8BFP0FcKrpx4U0aEC3qDZM5c+aeO2fmqo6he4KxTkTq6x8YHIoOx0ZGx8bjiYnJgmc3XI3nNduw3ZKqeNzQLZ4XujB4yXG5YqoGL6r1DX+/2OSup9vWnjh2eMVUapZ+qGuKIKqaiG9xY8lzuCZcu+YqZjUhsxQLYq4XpEMgI4xtO3GDfRzAhoYGTHBYEIQNKPDoKyMNBoe4ClrEuYT0YJ/jFDHSNiiLU4ZCbJ3+NVqVQ9aitV/TC9QanWLQcEk5hyR7ZLfshT2wO/bEPn6t1Qpq+F6OaVa7Wu5U42fTufd/VSbNAkdfqj89CxwiE3jVybsTMP4ttK6+eXL+klvfTbYW2CV7Jv8XrMPu6QZW81W73uG7bcSoAemfz90LCsup9GpqZWdZzmbCVkQxg3ks0nuvIYtNbCMf9KSNK1xH3qRZSZaS3VQpEmqm8C2k1CelNJAt Mel-spectrogram 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 Monotonic alignment search 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 Neural vocoder 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 HiFi-GAN AAACdnichVHLSgMxFD0d3/VVdSMIIpb6WFhuC2pxJbhxI9RHVVApM2OsQ+fFTFqpxR/wB1yICwUt4me48Qdc+AniUkEXLrydDoiKekOSk5N7bk4SzTUNXxI9RJSm5pbWtvaOaGdXd09vrK9/3XdKni5yumM63qam+sI0bJGThjTFpusJ1dJMsaEVF+r7G2Xh+YZjr8mKK3YstWAbe4auSqbysb6JJWFO+a7QpecUPNWazMfilKQgRn6CVAjiCCPrxGrYxi4c6CjBgoANydiECp/bFlIguMztoMqcx8gI9gWOEGVtibMEZ6jMFnks8GorZG1e12v6gVrnU0zuHitHkKB7uqZnuqMbeqT3X2tVgxp1LxWetYZWuPne48HV139VFs8S+5+qPz1L7CETeDXYuxsw9VvoDX358OR5dW4lUR2jC3pi/+f0QLd8A7v8ol8ui5VTRPkDUt+f+ydYTydTM8np5XR8PhN+RTuGMIoJfu9ZzGMRWeT43AOc4Qq1yJsyrCSU8UaqEgk1A/gSCn0Amu2Qkg== (Mel-spectrogram) 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 Encoder output 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 Target energy 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 Target log fo 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 Decoder input 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 Energy predictor 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 Energy Conv1D 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Extracting text, fundamental frequency and phoneme duration from musical sores Input text: Lyrics Fundamental frequency and phoneme duration: Notes Singing voice synthesis by using TTS model 9 Phoneme d e N d e N m u sh i m u sh i k a t a ts u m u r i Note G4 E4 Number of frames 12.5 25 Number of phonemes 1 1 37.5 2 25 2 37.5 2 12.5 2 25 2 25 2 25 2 50 2 G4 G4 C4 C4 C4 D4 37.5 2 12.5 2 25 2 E4 E4 D4 C4 D4 Input text Fundamental Frequency Phoneme duration When predicted durations of phonemes “d” and “e” are 6 and 10 frames, modi fi ed durations for SVS are 37.5 × 6 / (6 + 10) and 37.5 × 10 / (6 + 10) C4 261.63 Hz D4 293.67 Hz E4 329.63 Hz F4 349.23 Hz G4 392.00 Hz A4 440.00 Hz B4 493.88 Hz C5 523.25 Hz

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 Variance adapter 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 Comformer-based encoder 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 Embedding layer AAACcHichVHLSgMxFD0dX7U+WnVTcGG1KOKiZAQfuBLcuNTWqqBFMmNah87LmbTYFn/AH3Dhxgoi4me48Qdc+AniTgU3LrydDoiKekOSk5N7bk4SzTUNXzL2EFE6Oru6e6K9sb7+gcF4Ymh403cqni7yumM63rbGfWEatshLQ5pi2/UEtzRTbGnlldb+VlV4vuHYG7LmioLFS7ZRNHQuiSpsiCOZ4jY3a3Xh7SXSLMOCSP0EagjSCGPNSVxhF/twoKMCCwI2JGETHD61HahgcIkroEGcR8gI9gWOESNthbIEZXBiyzSWaLUTsjatWzX9QK3TKSZ1j5QpTLJ7ds1e2B27YY/s/ddajaBGy0uNZq2tFe5e/CSZe/tXZdEscfCp+tOzRBGLgVeDvLsB07qF3tZX66cvuaXsZGOKXbAn8t9kD+yWbmBXX/XLdZE9Q4w+QP3+3D/B5mxGnc/Mrc+mlxfDr4hiFBOYpvdewDJWsYY8nXuIU5yjGXlWksqYMt5OVSKhZgRfQpn5ADtBjyE= Text analyzer 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 Predicted acoustic feature 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 CFS2-based acoustic model 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 Output speech waveform 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 Musical score 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 Lyrics 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 Note 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 log fo 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 Duration 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 Mel-cepstrum 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 Mel-spectrogram 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 or 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 Monotonic alignment search 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 Neural vocoder 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 (Mel-spectrogram) 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 HiFi-GAN 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 Encoder output 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 Target energy 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 Target log fo 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 Decoder input 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 Energy predictor 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 Energy Conv1D 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 log fo predictor AAACgXicSyrIySwuMTC4ycjEzMLKxs7BycXNw8vHLyAoFFacX1qUnBqanJ+TXxSRlFicmpOZlxpaklmSkxpRUJSamJuUkxqelO0Mkg8vSy0qzszPCympLEiNzU1Mz8tMy0xOLAEKxQvIqMTk5KcrpMVXx+QmlmQU5Vbn19aqKDjn55UZusQLKBvoGYCBAibDEMpQZoCCgHyB5QwxDCkM+QzJDKUMuQypDHkMJUB2DkMiQzEQRjMYMhgwFADFYhmqgWJFQFYmWD6VoZaBC6i3FKgqFagiESiaDSTTgbxoqGgekA8ysxisOxloSw4QFwF1KjCoGlw1WGnw2eCEwWqDlwZ/cJpVDTYD5JZKIJ0E0ZtaEM/fJRH8naCuXCBdwpCB0IXXzSUMaQwWYLdmAt1eABYB+SIZor+savrnYKsg1Wo1g0UGr4HuX2hw0+Aw0Ad5ZV+SlwamBs1m4AJGgCF6cGMywoz0DM30TAKNlB0soFHBwSDNoMSgAQxvcwYHBg+GAIZQoL1NDCsYNjJsYmJm0mQyYDKCKGVihOoRZkABTNYAW6aT9w== log fo Conv1D 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 MSE 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 MSE 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 Duration predictor 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 Target duration 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 MSE AAACeXichVG9ThtBEP58JECcAAZSIKW5xCIyFNbcYdlOKks0KVIYHBskQNbdsZgV96e7tSVs8QK8QIo0SaQoMjxGGl6AgkeIUhIpRSiYOzuKUkBmtTuz38438+2uHboyVkRXGW3iwcPJqelH2cdPZmbncvMLrTjoRo5oOoEbRNu2FQtX+qKppHLFdhgJy7NdsWUfrSfnWz0RxTLw36njUOx5VseXB9KxFEPt3NPC26BjRVIdetLR9wPPkv5KO5en4qtq2SyVdSoSVQzTSAKzUlor6QYjieUxtnqQ+4pd7COAgy48CPhQHLuwEPPYgQFCyNgeBoxFHMn0XOAEWeZ2OUtwhsXoEa8d3u2MUZ/3Sc04ZTvcxeUZMVPHMl3SkK7pgs7pO93cWWuQ1ki0HLO3R1wRtudOlxq//svy2Csc/mXdq1nhANVUq2TtYYokt3BG/F7//XXj9eby4CV9ph+s/xNd0Te+gd/76XzZEJsfkOUP+PPK+t1Byywa5WJpw8zXquOvmMYzvECB37uCGt6gjib37eMjhjjL/NaeawVtdZSqZcacRfxj2tot00OSCg== (Logarithmic domain) 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 Duration of each note 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 Compensate AAACinichVE9TxtBEH0cJICB2ECDlOaEcURljS0DvqRBIkVKvgxIGFl3x9o+cXd7ultbIif/gfADKKiIFEVRqrShTJM/QMFPQJQg0VAwPl8UpSDMandm386bebtrBa4TKaKrIW145MXL0bHxzMTk1KtsbnpmJ5Kd0BY1W7oy3LPMSLiOL2rKUa7YC0JhepYrdq2jtf75bleEkSP9bXUciAPPbPlO07FNxVAjV1iou7KlNxtx3TNVO/Ri2est6LKpC9Nu60Fb+sITjVyeipWqUVla0alIiXFgGEaFqnopRfJIbV3mvqKOQ0jY6MCDgA/FsQsTEY99lEAIGDtAzFjIkZOcC/SQYW6HswRnmIwe8dri3X6K+rzv14wSts1dXJ4hM3UU6JK+0S39pu90TQ9P1oqTGn0tx+ytAVcEjeynua37Z1kee4X2X9Z/NSs0UU20Oqw9SJD+LewBv/vx9Hbr7WYhfkOf6Yb1n9MV/eIb+N07+8uG2DxDhj/gzyvrTwc75WJpubi0Uc6vVtOvGMNrzGOR33sFq/iAddS47wl+4CcutEmtrBnau0GqNpRyZvGPae8fAbqImCU= log fo of each phoneme 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 Training only 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 Inference for TTS only 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 Inference for SVS only 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 Gaussian 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 upsampling 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 Variance adapter Uni fi ed TTS and SVS framework 10

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Problem of SVS with baseline TTS model Low extrapolation accuracy of fundamental frequency and phoneme duration Proposed method with three modi fi cations Acoustic model: Baseline with phoneme embedding skip connection (PESC) Neural vocoder: FIRNet with source- fi lter vocoder (WORLD) features Input fundamental frequency shift Proposed method 11 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 (a) Fundamental frequency AAACeXichVG7SgNBFD1Z3/EVH4VgEw2RaBFmfWMl2Fgm0SSChrC7jjq4L3Y3AQ3+gD9gYaOCSPQzbPwBi3yCWCpYaOHdzYJoUO8wM2fO3HPnzIxq68L1GGtEpLb2js6u7p5ob1//wGBsaLjgWhVH43nN0i1nS1VcrguT5z3h6XzLdrhiqDovqodr/n6xyh1XWOamd2TzkqHsm2JPaIpHVDk2mlKn45kDy+QGj+9WnJBOsDQLIt4K5BAkEEbGit1gB7uwoKECAxwmPMI6FLjUtiGDwSauhBpxDiER7HOcIEraCmVxylCIPaRxn1bbIWvS2q/pBmqNTtGpO6SMI8keWZ29sAd2x57Yx6+1akEN38sRzWpTy+3y4OnYxtu/KoNmDwdfqj89e9jDcuBVkHc7YPxbaE199fjsZWMll6xNsSv2TP4vWYPd0w3M6qt2neW5c0TpA+Sfz90KCrNpeTG9kJ1NrM6HX9GNcUwiRe+9hFWsI4M8nXuMC9RxG3mXJqSUNNNMlSKhZgTfQpr7BNs6kY4= (b) Phoneme duration

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AAACbXichVHLSgMxFD0d3/VVFUFQpFh8rEpGUIurghvdtdXa4gOZGaMG58VMWqzFH3AtuBAFBRHxM9z4Ay78BHHhQsGNC2+nA6Ki3pDk5OSem5NEd03hS8YeIkpDY1NzS2tbtL2js6s71tO77Dslz+B5wzEdr6hrPjeFzfNSSJMXXY9rlm7ygr47V9svlLnnC8dekhWXr1vati22hKFJolYWbLck45LvyY1YgiVZEPGfQA1BAmFknNgV1rAJBwZKsMBhQxI2ocGntgoVDC5x66gS5xESwT7HAaKkLVEWpwyN2F0at2m1GrI2rWs1/UBt0CkmdY+UcYyye3bNXtgdu2GP7P3XWtWgRs1LhWa9ruXuRvfhwOLbvyqLZomdT9WfniW2kAq8CvLuBkztFkZdX94/flmczY1Wx9gFeyL/5+yB3dIN7PKrcZnluRNE6QPU78/9EyxPJtXp5FR2MpFOhV/RikGMYILeewZpzCODPJ1r4winOIs8K/3KkDJcT1UioaYPX0IZ/wBSSo3N Input text 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 Phoneme (+ accentual) sequence 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 Comformer-based decoder 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 Variance adapter 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 Comformer-based encoder 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 Embedding layer 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 Text analyzer 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 Output speech waveform 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 CFS2-based acoustic model 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 with PESC 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 Musical score 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 Lyrics 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 Note 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 log fo 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 Duration 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 Predicted WORLD feature 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 Mel-cepstrum 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 (log fo, V/UV, mel-cepstrum, band-aperiodicity) 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 Monotonic alignment search 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 Gaussian upsampling 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 Neural vocoder 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 (FIRNet) 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 Training only 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 Inference for TTS only AAACe3ichVHNSsNAEP4a/+tfVRDBS7AoIlKm0mrrSfCiN7W2CioliVsNppuQpIVafQFfwIMnBRHRt/DiC3jwEcSjghcFp2lEPKiz7M7st/PNfLurO5bp+USPEaWlta29o7Mr2t3T29cfGxgseHbFNUTesC3b3dQ1T1imFHnf9C2x6bhCK+uW2NAPFhvnG1XheqYt1/2aI3bK2p40S6ah+QwVY8PLsiRcIQ2hlmxXzRVyqi2tWjEWp0Qqk02l51RKUGAcZLPZFGXUZIjEEdqKHbvCNnZhw0AFZQhI+Bxb0ODx2EISBIexHdQZczkyg3OBY0SZW+EswRkaowe87vFuK0Ql7xs1vYBtcBeLp8tMFeP0QNf0Qvd0Q0/0/mutelCjoaXGXm9yhVPsPxnJvf3LKrP3sf/N+lOzjxIygVaTtTsB0riF0eRXD09fcvNr4/UJuqBn1n9Oj3THN5DVV+NyVaydIcof8PXK6u9BYSaRnE2kV2fiC5nwKzoxijFM8nvPYQFLWEGe+x7hAje4jXwocWVKmW6mKpGQM4QfpqQ/AXBRksE= Inference for SVS only For improving phoneme expansion accuracy Monotonic alignment search is trained with
 embedding features instead of encoded features Phoneme embedding skip connection 12

Slide 13

Slide 13 text

Excitation generator Residual FIR network Resonance FIR network Speech waveform Concatenate Causal conv block Causal conv block MGC V/UV Cont. log fO BAP Mixed excitation Input features Residual signal Causal conv block (a) Network architecture N V C B M Fundamental frequency controllable neural vocoder (Ohtani+ ICASSP 2024) Two types of FIR fi lter are trained with neural networks Simple excitation signal is convulsed with these FIR fi lters Fast inference compared with other models
 e.g. Harmonic-Net+, Si-Fi-GAN Demo samples
 fo x 1.0
 
 fo x 0.5
 
 fo x 2.0 FIRNet neural vocoder 13 Speech demo samples

Slide 14

Slide 14 text

For improving fundamental frequency prediction accuracy Converting input fundamental frequency
 inside the range of training data Shit amount is calculated from mean value
 in training set and intermediate value in
 synthesized songs Input fundamental frequency shift 14 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 Phoneme (+ accentual) sequence 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 Comformer-based decoder 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 Variance adapter 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 Comformer-based encoder 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 Embedding layer 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 Text analyzer 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 CFS2-based acoustic model 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 with PESC 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 Musical score 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 Lyrics 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 Note 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 Duration 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 Predicted WORLD feature AAACeXichVG7SgNBFD1Z3/EVH4VgEw2KWISJgoqVYKFlfEQDUcLsOsbBfbGzG9DgD/gDFjYqiEQ/w8YfsPATxFLBQgvvbhZERb3Lzpw5c8+9Z2Z015TKZ+whoTU1t7S2tXckO7u6e3pTff0bygk8QxQMx3S8os6VMKUtCr70TVF0PcEt3RSb+v5iuL9ZFZ6Sjr3uH7hi2+IVW+5Kg/tElVODSzxQSnI7HbiKW9TSriTLqQzLsijSP0EuBhnEkXdSV9jCDhwYCGBBwIZP2ASHoq+EHBhc4rZRI84jJKN9gSMkSRtQlqAMTuw+jRValWLWpnVYU0Vqg7qY9HukTGOM3bM6e2Z37IY9svdfa9WiGqGXA5r1hla45d7jobXXf1UWzT72PlV/evaxi7nIqyTvbsSEpzAa+urhyfPa/OpYbZxdsCfyf84e2C2dwK6+GJcrYvUU4QPkvl/3T7Axlc3NZGdWpjILc/FTtGMYo5ig+57FApaRR4H6HuIMdVwn3rQRbUKbbKRqiVgzgC+hTX8A6r2SEw== Gaussian upsampling 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 log(fo fshift) AAACunichVHLbhMxFD0dXiU8GmCDxGZEWpRKSXAqAVXFohIbln0waaWmijyOk1jxjEczTqQwmh/oD3TRFUgIIT6BJRt+gEWXLKHLIrFhwc1kJB4VcC3bx8f3XB/bfqRVYhk7nnPOnb9w8dL85dKVq9euL5Rv3GwlZhQL6QmjTbzr80RqFUrPKqvlbhRLHvha7vjDJ9P9nbGME2XCZ3YSyf2A90PVU4Jbojplr7rY1qbvVnudtB1wO4iD1GSZW3d/IZKB6tksW16sua37XqvmBlLXhYwSG4+CmuvzsFvnkYyV6Sqh7GS5U66wBsvDPQuaBaigiA1Tfo02ujAQGCGARAhLWIMjobaHJhgi4vaREhcTUvm+RIYSaUeUJSmDEzuksU+rvYINaT2tmeRqQado6jEpXSyxj+wNO2Uf2Fv2mX3/a600rzH1MqHZn2ll1Fk4uL397b+qgGaLwU/VPz1b9LCae1XkPcqZ6S3ETD9+fni6vba1lN5jL9kJ+X/Bjtl7ukE4/ipebcqtI5ToA5p/PvdZ0FppNB82HmyuVNZXi6+Yxx3cRZXe+xHW8RQb8Ojcd/iELzhxHju+o5zhLNWZKzS38Fs49gfo+KqI (log(fo fshift), V/UV, mel-cepstrum, band-aperiodicity) 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 +fshift AAACnnichVFLS1tBGD1eWx+pj2g3gptLo8VCEidCW3UlCMWN1FdiQCXMnUx08L6YOwnES/6Af6CLLkoLpUh/hhS6aldd+BPEpYVuXPjl5kKp0vYbZubMme98c2bGCV0VGcYu+qz+Bw8HBoeGM49GRsfGsxOTlShoaiHLInADXXV4JF3ly7JRxpXVUEvuOa7cdY5Xu/u7LakjFfg7ph3KA48f+qqhBDdE1bJLczONWrzvcXOkvTjodGbydmW+XMnbnnQLQoaR0U0vbzvcrxd4KLUK6koo035Wy+ZYkSVh3welFOSQxkaQ/YR91BFAoAkPEj4MYRccEbU9lMAQEneAmDhNSCX7Eh1kSNukLEkZnNhjGg9ptZeyPq27NaNELegUl7ompY1Z9oOdsWv2lX1ml+zmr7XipEbXS5tmp6eVYW38dGr7139VHs0GR79V//Rs0MBi4lWR9zBhurcQPX3r5M319vLWbPyUfWBX5P89u2DndAO/9VN83JRbb5GhDyjdfe77oLJQLL0oPt9cyK0spl8xhGk8wRy990usYA0bKNO57/AF3/Ddsq1X1rr1updq9aWax/gjrOotjMafPA== (fo, V/UV, mel-cepstrum, band-aperiodicity)

Slide 15

Slide 15 text

Experimental conditions Speech Corpus: JSUT for training and evaluation and JSUT-song only for evaluation Sampling frequency: 24 kHz Trained and inferred PyTorch 2.0.1 Trained using an NVIDIA Tesla A100 GPU with 40 GB of memory ESPnet2-TTS recipe for JSUT corpus Frame shift: 10 ms 120 beats per minute for SVS Input fundamental frequency shift: 261.6 + (523.3 − 261.6) / 2 − 206 = 186.5 Hz Experiments 15 Mean value of training data Intermediate value of synthesized songs

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Results of objective evaluations 16 Table 1: Results of objective evaluations. The values in the columns for mel-cepstral distortion (MCD) and log fo root-mean-square error (RMSE) are the means and standard deviations. AM and NV represent acoustic model and neural vocoder, respectively. TTS SVS AM NV Input fo shift Acoustic feature MCD [dB] log fo RMSE MCD [dB] log fo RMSE CFS2 HiFi-GAN mel-spectrogram 6.20 ± 0.49 0.22 ± 0.06 11.4 ± 0.83 0.41 ± 0.14 CFS2 HiFi-GAN WORLD 6.39 ± 0.51 0.22 ± 0.06 12.0 ± 1.08 0.41 ± 0.10 PESC HiFi-GAN WORLD 6.35 ± 0.51 0.22 ± 0.06 11.5 ± 1.17 0.37 ± 0.09 PESC HiFi-GAN √ WORLD - - 10.9 ± 0.92 0.57 ± 0.15 CFS2 FIRNet WORLD 6.41 ± 0.50 0.23 ± 0.06 12.2 ± 1.02 0.35 ± 0.10 PESC FIRNet WORLD 6.39 ± 0.49 0.23 ± 0.06 11.6 ± 1.18 0.34 ± 0.09 PESC FIRNet √ WORLD - - 10.5 ± 1.00 0.30 ± 0.11 els. The JSUT-Song corpus was used only for evaluating the SVS model. Following the procedure established for ESPnet2- TTS [8], 4,500 utterances, 250 utterances, and 250 utterances were used for the training set, validation set, and test set for TTS, respectively. For TTS in Japanese, the G2P function based on pyopenjtalk and enhanced with prosody symbols [34] was used, following [8, 11]. For the subjective evaluations of TTS, 10 utterances were randomly selected. For the objective and subjective evaluations of SVS, the first phrases of 10 songs from lated by the ESPnet2-TTS toolkit [8, 9]. To evaluate the syn- thesized TTS and SVS speech subjectively, mean opinion score (MOS) tests [38] were conducted for (a) normal TTS, (b) nor- mal SVS, (c) T × 0.5 SVS (240 beats per minute), (d) fo × 0.5 SVS (−1 octave), and (e) fo × 2.0 SVS (+1 octave). In (d) and (e), fo was controlled before the neural vocoders. Each sub- ject evaluated 200 samples: 10 utterances × 20 models. The naturalness of each sample was rated on a five-point scale: (1) bad, (2) poor, (3) fair, (4) good, and (5) excellent. Twenty adult

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Slide 18

Slide 18 text

Proposed method: Uni fi ed TTS and SVS models only using TTS data Phoneme embedding skip connection -> improving duration control FIRNet neural vocoder with WORLD features -> extrapolating fundamental frequency Input fundamental frequency shift -> improving fundamental frequency control Conclusion 18 Speech demo samples