博碩士論文 104552021 詳細資訊




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姓名 朱祥豪(Hsiang-Hao Chu)  查詢紙本館藏   畢業系所 資訊工程學系在職專班
論文名稱 高品質口述系統之設計與應用
(The Design and Application of High Quality Spoken System)
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摘要(中) 本論文主要是研究基於神經網路之高品質口述系統的技術,並延伸相關的設計與應用,與以往最大不同的是,現今我們擁有更多的訓練資料、更快速的硬體設備、以及更多樣可搭配在語音合成的其他增強技術,讓合成語音的品質更加貼近真人聲音。要使這項技術能應用於生活上,需要設計具彈性且支援多方技術的工具來供實作,本系統主要是用Python語言開發,安裝在Linux作業系統上,需要一個可支援外部前端功能的工具,前端輸出的格式必須為狀態層次校準(state-level alignment)的HTS標籤,目前支援兩個語音編碼器(vocoder):STRAIGHT和WORLD,在訓練神經網絡之前,對語言特徵使用min-max正規化,而輸出聲學特徵則是採用mean-variance正規化。至於聲學建模(Acoustic Modelling)的原理,則是採用前饋神經網路(Feedforward Neural Network)和基於遞歸神經網路之長短期記憶(Long Short-Term Memory based RNN)於系統中實現。另外,就本系統的特色與長處,分別介紹三種相關的應用。最後,也期待這系統,除了不斷地在品質及效能上精進之外,也能推展到台灣各個有需要的地方。
摘要(英) This paper focuses on the technology of high quality dictation system based on neural network and extends the related design and application. The biggest difference is that we have more training materials, faster hardware and more Variety can be used in the voice synthesis of other enhanced technology, so that the quality of synthetic speech more close to the real voice. To make this technology can be applied to life, the need to design flexible and support multi-technology tools for implementation, the system is mainly developed in Python language, installed on the Linux operating system, you need a support for external front-end features Tools, the front-end output format must be state-level alignment of the HTS tag, currently supports two voice coder (vocoder): STRAIGHT and WORLD, before training the neural network, the language features using min-max regular And the output acoustic feature is normalized with mean-variance. As for the principle of Acoustic Modeling, the Feedforward Neural Network and Long Short-Term Memory based (RNN) are implemented in the system. In addition, the characteristics and strengths of the system, respectively, introduced three related applications. Finally, it is also looking forward to this system, in addition to constantly in the quality and efficiency on the sophisticated, but also to promote the various needs of Taiwan.
關鍵字(中) ★ 口述 關鍵字(英)
論文目次 中文摘要 I
英文摘要 II
致謝 III
章節目錄 IV
圖目錄 VI
表目錄 VII
第一章 緒論 1
1.1 研究動機 1
1.2 研究目的 1
1.3 研究背景 2
第二章 系統架構 4
2.1 語音合成工具 4
2.2 聲學建模(ACOUSTIC MODELLING) 5
2.3 系統實現 8
第三章 系統實作 10
3.1 環境部署 10
3.2 軟體安裝 11
3.3 訓練資料 13
3.4 實作結果 16
第四章 系統相關應用介紹 19
4.1 應用於聽取新聞 19
4.2 應用於電玩智能配音 19
4.3 應用於智慧童話書 21
第五章 結論與展望 23
參考文獻 24
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[16] B. Uria, I. Murray, S. Renals, and C. Valentini, “Modelling acoustic feature dependencies with artificial neural networks: Trajectory-rnade,” in Proc. IEEE Int. Conf. on Acoustics, Speech, and Signal Processing (ICASSP), 2015, pp. 4465–4469.

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[20] Z. Wu, C. Valentini-Botinhao, O. Watts, and S. King,“Deep neural networks employing multi-task learning and stacked bottleneck features for speech synthesis,” in Proc. IEEE Int. Conf. on Acoustics, Speech, and Signal Processing (ICASSP), 2015, pp. 4460–4464.

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[22] O. Watts, G. E. Henter, T. Merritt, Z. Wu, and S. King,“From HMMs to DNNs: where do the improvements come from?” in Proc. IEEE Int. Conf. on Acoustics, Speech, and Signal Processing (ICASSP), 2016.

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[25] Y. Fan, Y. Qian, F. K. Soong, and L. He, “Sequence generation error (SGE) minimization based deep neural networks training for text-to-speech synthesis,” in Proc. Interspeech, 2015, pp. 864–868.

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[27] Y. Fan, Y. Qian, F. Xie, and F. K. Soong, “TTS synthesis with bidirectional LSTM based recurrent neural networks,” in Proc. Interspeech, 2014, pp. 1964–1968.

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[29] Zhizheng Wu, Oliver Watts, Simon King, “Merlin: An Open Source Neural Network Speech Synthesis System,” in Proc. 9th ISCA Speech Synthesis Workshop (SSW9), September 2016, Sunnyvale, CA, USA.

[30] Z. Wu and S. King, “Investigating gated recurrent neural networks for speech synthesis,” in Proc. IEEE Int. Conf. on Acoustics, Speech, and Signal Processing (ICASSP), 2016.

[31] SPTK官方網站, http://sp-tk.sourceforge.net/

[32] T. Merritt, R. A. Clark, Z. Wu, J. Yamagishi, and S. King,“Deep neural network-guided unit selection synthesis,” in Proc. IEEE Int. Conf. on Acoustics, Speech, and Signal Processing (ICASSP), 2016.

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[34] M. MORISE, F. YOKOMORI, and K. OZAWA,“WORLD: a vocoder-based high-quality speech synthesis system for real-time applications,” IEICE transactions on information and systems, 2016.

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[36] S. Hochreiter and J. Schmidhuber, “Long short-term memory,” Neural computation, vol. 9, no. 8, pp. 1735–1780, 1997.

[37] A. Graves and J. Schmidhuber, “Framewise phoneme classification with bidirectional LSTM and other neural network architectures,” Neural Networks, vol. 18, no. 5, pp. 602–610, 2005.

[38] Festival官網下載網址, http://festvox.org/packed/festival/2.4/

[39] Merlin提供的訓練資料下載連結,http://104.131.174.95/slt_arctic_full_data.zip

[40] 陰陽師官網, https://www.onmyojigame.com/#2

[41] Merlin相關討論文章, https://github.com/CSTR-Edinburgh/merlin/issues/18

[42] 市面上販售有聲故事書, http://shopping.windmill.com.tw/product.php?product_num=10155936
指導教授 王家慶 審核日期 2017-7-25
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