Transcription/pitch estimation (audio to symbolic)

• Kim et al.
• Krause et al.
• Perez et al.
• Riou et al. - ISMIR 2023 best paper award
• Shao et al.
• Tamer et al.
• Toyama et al.
• Zeitler et al.
• Zhuo et al.

Score following/alignment (symbolic)

• Peter

Generation (symbolic)

• Bjare et al.
• Malandro
• Min et al.
• Van Kranenburg and Kearns

Generation (audio)

• Borovik and Viro
• Flores Garcia et al.
• Serra et al.

Sound matching (audio to synthesizer parameters)

• Barkan et al.
• Yang et al.

Music modeling (symbolic)

• Fradet et al.

Optical music recognition (images to symbolic)

• Castellanos et al.
• Martinez-Sevilla et al.
• Penarrubia et al.

Music information retrieval (text and symbolic)

• Ferraro et al.
• Wu et al. - ISMIR 2023 best student paper award

Source separation (audio to audio)

• Nakano et al.
• Plaja-Roglans et al.

Performance analysis (audio to symbolic)

• Alonso-Jimenez et al.
• Buisson et al.
• Cheng et al.
• Doh et al.
• Han et al.
• Krause et al.
• Ma et al.
• Morsi et al.
• Torres et al.

Score analysis (symbolic to symbolic)

• Borsan et al.
• Couturier et al.
• Foscarin et al.
• Hajic et al.
• Miller et al.
• Karystinaios and Widmer
• Zhang et al.

Datasets

• Amatov et al. - music fragments paired with hummed versions
• Arthur et al. - melodic and harmonic transcriptions
• Hsiao et al. - repeated symbolic patterns
• Hu et al. - audio-symbolic aligned piano performances
• Jiang - piano performances with human evaluations
• Lustig and Temperley - musical excerpts with analysis and comments
• Pereira et al. - source separation
• Riley and Dixon - audio-symbolic aligned bassline performances

Ethics

• Dinnisson and Bauer
• Morreale et al. - ISMIR 2023 responsible AI award Resources and Tools
• Carriero et al. meta ontology
• Hentschel et al. DiMCAT
• Lewis et al. tools for dataset curation
• Moises commercial application