Titulo Estágio
Audio Fingerprinting and Music Identification
Área Tecnológica
Multimédia
Local do Estágio
DEI
Enquadramento
Music identification systems aim to recognize songs based on their playback in moderate noisy environments. In most current platforms (e.g., Shazam, Gracenote MusicID, 411-Song), you dial the number of the service provider with your cell phone, hold your phone towards the source of the music for a few seconds (from 3 to 20, depending on the provider) and then wait for a message containing the identification of the song (artist, title, etc.). Such applications are based on audio fingerprinting techniques, where an individual signature is extracted for each song in the database, and then compared with the fingerprint computed for the query sample.
Objetivo
Present challenges in the area include the identification of songs in disturbed conditions, e.g., noisy environments, poor recordings, etc., or using only a few seconds of audio for matching.
The main objective of this thesis is to improve the state of the art on music identification by investigating and extending the current techniques and proposing new approaches to the problem (e.g., hashing and search techniques, feature extraction approaches, etc.)
References:
- Eugene Weinstein and Pedro Moreno (2007). “Music Identification with Weighted Finite-State Transducers”, Proceedings of the International Conference on Acoustics, Speech, and Signal Processing (ICASSP) 2007.
- Jaap Haitsma and Ton Kalker. (2002). “A highly robust audio-fingerprinting systems”. Proceedings of the 3rd International Conference on Music Information Retrieval.
- Avery Wang (2003). “An industrial-strength audio search algorithm”. Proceedings of the 4th International Conference on Music Information Retrieval, invited talk.
Plano de Trabalhos - Semestre 1
1. Study and summarization of the state-of-the art.
2. Requirements analysis.
3. Review of feature extraction.
4. Review of matching techniques.
5. Design of the graphical user interface.
6. Documentation (in each stage) and intermediate report.
Plano de Trabalhos - Semestre 2
1. Implementation of feature extraction.
2. Implementation of matching techniques.
3. Implementation of the graphical user interface.
4. System evaluation: accuracy, computational efficiency, …
5. Software tests.
6. Documentation (in each stage) and thesis writing.
7. Writing of a scientific article.
(8. Design, implementation and evaluation of new approaches to the problem. (if time permits))
Condições
Estágio não remunerado.
Orientador
Rui Pedro Paiva
ruipedro@dei.uc.pt 📩