Automatic Evaluation of Karaoke Singing Based on Pitch, Volume, and Rhythm Features

Tsai, Wei-Ho; Lee, Hsin-Chieh

doi:10.1109/tasl.2011.2174224

Cited by 44 publications

(29 citation statements)

References 13 publications

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“…The proposed singing evaluation system is built on using CD music as a reference basis. This differs from the work in [9], which used Karaoke VCD music as the reference basis, and the work in [3], which used MIDI files as the reference basis.…”

Section: Introductionmentioning

confidence: 84%

“…Although so far there have been several studies [1][2][3][4][5][6][7][8][9] to this end, most of them are reported in patent documentation, which only describe their implementation details and fail to present the theoretical foundation and qualitative analysis conducted to validate their methods. Only very few studies are reported in scientific literature.…”

Section: Introductionmentioning

confidence: 99%

“…Only very few studies are reported in scientific literature. The most thorough investigation of this research topic is a work reported in [9]. It comprehensively discusses the strategies and acoustic cues for singing performance evaluation.…”

Section: Introductionmentioning

confidence: 99%

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Singing performance evaluation by reference to CD music recordings

Tsai

Ma²

2014

2014 IEEE International Conference on Consumer Electronics - Taiwan

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This paper proposes an automatic system that rates a singing performance by comparing it with the vocal pitch in a referential CD music recording. The system allows users to not only enjoy listening to and singing with CD songs but also know how well or bad they sing. To this end, our special efforts are put on extracting the pitch-based features of the original singer in the accompanied vocals. Our experiment shows that the results of the proposed singing evaluation system are close to the human rating.

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Section: Introductionmentioning

confidence: 84%

Section: Introductionmentioning

confidence: 99%

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Singing performance evaluation by reference to CD music recordings

Tsai

Ma²

2014

2014 IEEE International Conference on Consumer Electronics - Taiwan

Self Cite

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“…It also differs from post-singing performance appraisal [32] which requires singing to be performed in the first place. In our preliminary studies [21], [22], we formulated the scientific problem of competence-based song recommendation, proposing a novel solution and demonstrated a system for karaoke song recommendation.…”

Section: Song Recommendationmentioning

confidence: 99%

Competence-Based Song Recommendation: Matching Songs to One’s Singing Skill

Mao

Shou

Fan

et al. 2015

IEEE Trans. Multimedia

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Singing is a popular social activity and a pleasant way of expressing one's feelings. One important reason for unsuccessful singing performance is because the singer fails to choose a suitable song. In this paper, we propose a novel competence-based song recommendation framework for the purpose of singing. It is distinguished from most existing music recommendation systems which rely on the computation of listeners' interests or similarity. We model a singer's vocal competence as a singer profile, which takes voice pitch, intensity, and quality into consideration. Then we propose techniques to acquire singer profiles. We also present a song profile model which is used to construct a human annotated song database. Then we propose a learning-to-rank scheme for recommending songs by a singer profile. Finally, we introduce a reduced singer profile which can greatly simplify the vocal competence modelling process. The experimental study on real singers demonstrates the effectiveness of our approach and its advantages over two baseline methods.

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“…There are many reports of research on automatic estimation of singing characteristics from audio signals: characteristics such as voice category (e.g., soprano or alto) [6,7], gender [8][9][10], age [10], body size [10], race [10], vocal register [11], singing modeling (F0, power, and spectral envelope) [12][13][14][15][16][17][18][19], breath sound [20,21], singing skill [6,7,[22][23][24][25], enthusiasm [26], F 0 dynamics and musical genres [27], and the language of the lyrics [28][29][30][31] have been previously proposed. The above previous works, however, have not revealed latent topics that are shared by different singing voices.…”

Section: Introductionmentioning

confidence: 99%

Vocal timbre analysis using latent Dirichlet allocation and cross-gender vocal timbre similarity

Nakano

Yoshii

Goto

2014

2014 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)

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This paper presents a vocal timbre analysis method based on topic modeling using latent Dirichlet allocation (LDA). Although many works have focused on analyzing characteristics of singing voices, none have dealt with "latent" characteristics (topics) of vocal timbre, which are shared by multiple singing voices. In the work described in this paper, we first automatically extracted vocal timbre features from polyphonic musical audio signals including vocal sounds. The extracted features were used as observed data, and mixing weights of multiple topics were estimated by LDA. Finally, the semantics of each topic were visualized by using a word-cloud-based approach. Experimental results for a singer identification task using 36 songs sung by 12 singers showed that our method achieved a mean reciprocal rank of 0.86. We also proposed a method for estimating cross-gender vocal timbre similarity by generating pitch-shifted (frequency-warped) signals of every singing voice. Experimental results for a cross-gender singer retrieval task showed that our method discovered interesting similar pitch-shifted singers.

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Automatic Evaluation of Karaoke Singing Based on Pitch, Volume, and Rhythm Features

Cited by 44 publications

References 13 publications

Singing performance evaluation by reference to CD music recordings

Singing performance evaluation by reference to CD music recordings

Competence-Based Song Recommendation: Matching Songs to One’s Singing Skill

Vocal timbre analysis using latent Dirichlet allocation and cross-gender vocal timbre similarity

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