The Harmonic Shift Algorithm for Efficient Multi-Pitch Detection

Grinewitschus, Lukas; Jung, Peter

doi:10.1109/taslp.2021.3129344

Cited by 3 publications

(2 citation statements)

References 22 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Other works such as that by Grinewitschus et al [21] report speed as a multiplier of the "realtime", which is the duration of the audio segment to be evaluated. Their approach, based on leveraging the constant-Q Gabor Transform followed by harmonic shift algorithms and corrective heuristics, reaches a declared 0.29 × realtime speed on a more powerful machine than what has been used in the present work; nonetheless, OBP reaches 0.046 × realtime.…”

Section: Discussionmentioning

confidence: 99%

“…Attempts at fast pitch detectors are based on the simplification of the transformation procedures, such as the work by Grinewitschus et al [21], which leverages the constant-Q Gabor transform for a threshold-based approach within a four-dimensional logarithmic harmonic spectrum shift. A work by Mnasri et al [22] aims to avoid short-time analysis and thus the underlying approximations about local stationarity by employing the Hilbert transform to derive "instantaneous" frequency components to contour F0: the performances might be comparable to YIN or SWIPE, but no indication on speed is given.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

OneBitPitch (OBP): Ultra-High-Speed Pitch Detection Algorithm Based on One-Bit Quantization and Modified Autocorrelation

Coccoluto,

Cesarini,

Costantini

2023

Applied Sciences

View full text Add to dashboard Cite

This paper presents a novel, high-speed, and low-complexity algorithm for pitch (F0) detection, along with a new dataset for testing and a comparison of some of the most effective existing techniques. The algorithm, called OneBitPitch (OBP), is based on a modified autocorrelation function applied to a single-bit signal for fast computation. The focus is explicitly on speed for real-time pitch detection applications in pitch detection. A testing procedure is proposed using a proprietary synthetic dataset (SYNTHPITCH) against three of the most widely used algorithms: YIN, SWIPE (Sawtooth Inspired Pitch Estimator) and NLS (Nonlinear-Least Squares-based). The results show how OBP is 9 times faster than the fastest of its alternatives, and 50 times faster than a gold standard like SWIPE, with a mean elapsed time of 4.6 ms, or 0.046 × realtime. OBP is slightly less accurate for high-precision landmarks and noisy signals, but its performance in terms of acceptable error (<2%) is comparable to YIN and SWIPE. NLS emerges as the most accurate, but it is not flexible, being dependent on the input and requiring prior setup. OBP shows to be robust to octave errors while providing acceptable accuracies at ultra-high speeds, with a building nature suited for FPGA (Field-Programmable Gate Array) implementations.

show abstract

Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

OneBitPitch (OBP): Ultra-High-Speed Pitch Detection Algorithm Based on One-Bit Quantization and Modified Autocorrelation

Coccoluto,

Cesarini,

Costantini

2023

Applied Sciences

View full text Add to dashboard Cite

show abstract

Identification of Multiple Events Based on Two-Dimensional Images and Isotropic Network in Optical Fiber Perimeter Security System

Sun,

Fang,

Dai

et al. 2024

IEEE Sensors J.

View full text Add to dashboard Cite

Multipitch estimation based on the iterative detection and separation of note events from single-channel polyphonic recordings

Delgado Castro,

Szymanski

2023

The Journal of the Acoustical Society of America

View full text Add to dashboard Cite

Multiple fundamental frequency estimation has been extensively used in applications such as melody extraction, music transcription, instrument identification, and source separation. This paper presents an approach based on the iterative detection and extraction of note events, which are considered to be harmonic sounds characterised by a continuous pitch trajectory. Note events are assumed to be associated with musical notes being played by a single instrument, and their pitch trajectories are iteratively estimated. In every iteration, the pitch contour of the predominant note event is selected from a set of pitch estimates and used to separate its spectral energy from the input mixture in order to obtain a residual signal, which is then used as input in the next iteration. This iterative process stops when the energy of the residual is below a significance threshold. The pitch trajectories of all detected note events are then revised and reassembled to form the final set of pitch estimates for the original audio input. Evaluation of performance is conducted in different scenarios to show the potential of the proposed system, both in terms of its accuracy, and also as an initial stage in other complex tasks, such as note tracking and multipitch streaming.

show abstract

The Harmonic Shift Algorithm for Efficient Multi-Pitch Detection

Cited by 3 publications

References 22 publications

OneBitPitch (OBP): Ultra-High-Speed Pitch Detection Algorithm Based on One-Bit Quantization and Modified Autocorrelation

OneBitPitch (OBP): Ultra-High-Speed Pitch Detection Algorithm Based on One-Bit Quantization and Modified Autocorrelation

Identification of Multiple Events Based on Two-Dimensional Images and Isotropic Network in Optical Fiber Perimeter Security System

Multipitch estimation based on the iterative detection and separation of note events from single-channel polyphonic recordings

Contact Info

Product

Resources

About