Recognition of Isolated Instrument Tones by Conservatory Students
نویسندگان
چکیده
An experiment was conducted in order to reconstruct previous timbre recognition experiments, measure the effect of ensemble experience and short-term training on the recognition rate, and generate more detailed baseline data to help evaluate the performance of timbre recognition computer models. The subjects, who were conservatory students, had to identify between 2, 3, 9, and 27 instruments on two different occasions: once without practice and once with short training sessions before the test. Eighty-eight subjects participated in the experiment. All tones were taken from the McGill University Master Samples CDs. Compared to previous experiments, the average scores of subjects in this experiment were considerably higher. Additionally, subjects who play orchestral instruments scored significantly higher than those who do not. Finally, the short training sessions had no significant effect on the subjects’ performance.
منابع مشابه
Absolute pitch among students at the Shanghai Conservatory of Music: a large-scale direct-test study.
This paper reports a large-scale direct-test study of absolute pitch (AP) in students at the Shanghai Conservatory of Music. Overall note-naming scores were very high, with high scores correlating positively with early onset of musical training. Students who had begun training at age ≤5 yr scored 83% correct not allowing for semitone errors and 90% correct allowing for semitone errors. Performa...
متن کامل2 pMU 9 . Musical instrument identification : A pattern - recognition approach
A statistical pattern-recognition technique was applied to the classification of musical instrument tones within a taxonomic hierarchy. Perceptually salient acoustic features— related to the physical properties of source excitation and resonance structure—were measured from the output of an auditory model (the log-lag correlogram) for 1023 isolated tones over the full pitch ranges of 15 orchest...
متن کاملSpecific Music Transcription for Tutoring
An applicationspecific, musictranscription approach uses a customized human– computer interface to combine the strengths of humans and computers to enhance music transcription through instrument modeling and multimedia fusion. A utomatic music transcription (AMT) refers to the ability of computers to write note information—such as the pitch, onset time, duration, and source of each sound— after...
متن کاملMusical Instrument Recognition and Classification Using Time Encoded Signal Processing and Fast Artificial Neural Networks
Traditionally, musical instrument recognition is mainly based on frequency domain analysis (sinusoidal analysis, cepstral coefficients) and shape analysis to extract a set of various features. Instruments are usually classified using k-NN classifiers, HMM, Kohonen SOM and Neural Networks. In this work, we describe a system for the recognition of musical instruments from isolated notes. We are i...
متن کاملFrequency-Zooming ARMA Modeling for Analysis of Noisy String Instrument Tones
This paper addresses model-based analysis of string instrument sounds. In particular, it reviews the application of autoregressive (AR) modeling to sound analysis/synthesis purposes. Moreover, a frequency-zooming autoregressive moving average (FZ-ARMA) modeling scheme is described. The performance of the FZ-ARMA method on modeling the modal behavior of isolated groups of resonance frequencies i...
متن کامل