연구동향 분석

A Comparison of L1 and L2 Speech Phonetic Posteriorgrams for Applications in Pronunciation Training

조영선 남호성 2021년

논문상세정보
인용/피인용
' A Comparison of L1 and L2 Speech Phonetic Posteriorgrams for Applications in Pronunciation Training' 의 주제별 논문영향력
논문영향력 선정 방법
논문영향력 요약
주제
  • Accent Conversion
  • Computer-Assisted Pronunciation Training
  • Phonetic Posteriorgram
  • 억양 변환
  • 음성변환
  • 음소사후확률
  • 컴퓨터 보조 발음 교육
동일주제 총논문수 논문피인용 총횟수 주제별 논문영향력의 평균
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' A Comparison of L1 and L2 Speech Phonetic Posteriorgrams for Applications in Pronunciation Training' 의 참고문헌

  • 몽골인 한국어 학습자들의 한국어 이중모음 오류 분석
    노채환 [2020]
  • “아는 게 많을수록 외국어 학습에 좋을까?” -모음 음소 목록의 크기와 새로운 모음의 지각을 중심으로-
    홍승아 [2019]
  • Voice conversion using deep bidirectional long short-term memory based recurrent neural networks
    Sun, L. [2015]
  • Voice conversion based on maximum-likelihood estimation of spectral parameter trajectory
    Toda, T. [2007]
  • Voice Conversion Across Arbitrary Speakers Based on a Single Target-Speaker Utterance
    Liu, S. [2018]
  • Visualizing data using t-SNE
  • Using phonetic posteriorgram based frame pairing for segmental accent conversion
    Zhao, G. [2019]
  • Using dynamic time warping to find patterns in time series
    Berndt, D. [1994]
  • Unsupervised discovery of non-native phonetic patterns in l2 english speech for mispronunciation detection and diagnosis
    Li, X. [2018]
  • Unsupervised discovery of an extended phoneme set in l2 english speech for mispronunciation detection and diagnosis
    Mao, S. [2018]
  • The CMU Arctic Databases for Speech Synthesis
    Kominek, J. [2004]
  • Phonetic posteriorgrams for many-to-one voice conversion without parallel data training
    Sun, L. [2016]
  • Personalized, Cross-Lingual TTS Using Phonetic Posteriorgrams
    Sun, L. [2016]
  • Montreal Forced Aligner: Trainable Text-Speech Alignment Using Kaldi
  • Mispronunciation detection via dynamic time warping on deep belief network-based posteriorgrams
    Lee, A. [2013]
  • Locally Linear Embedding for Exemplar-Based Spectral Conversion
    Wu, Y. C. [2016]
  • Librispeech: an asr corpus based on public domain audio books
  • L2-ARCTIC: A non-native English speech corpus
    Zhao, G. [2018]
  • Jointly Trained Conversion Model and WaveNet Vocoder for Non-Parallel Voice Conversion Using Mel-Spectrograms and Phonetic Posteriorgrams
    Liu, S. [2019]
  • Improving deep neural network acoustic models using generalized maxout networks
    Zhang, X. [2014]
  • Golden speaker builder – An interactive tool for pronunciation training
    Ding, S. [2019]
  • Foreign accent conversion in computer assisted pronunciation training
    Felps, D. [2009]
  • Foreign Accent Conversion by Synthesizing Speech from Phonetic Posteriorgrams
    Zhao, G. [2019]
  • Exemplar selection methods in voice conversion
    Zhao, G. [2017]
  • Enhancing foreign language tutors–in search of the golden speaker
    Probst, K. [2002]
  • Data mining
    Han, J. [2012]
  • Cross-lingual voice conversion with bilingual phonetic posteriorgram and average modeling
    Zhou, Y. [2019]
  • Can voice conversion be used to reduce non-native accents?
    Aryal, S. [2014]
  • Automatic Pronunciation Evaluation of Singing
    Gupta, C. [2018]
  • A comparative study on system combination schemes for LVCSR
    Ma, C. [2010]