Fundamental frequency estimation based on pitch-scaled harmonic filtering
- Authors: Sergio Roa, Maren Bennewitz, and Sven Behnke
- In Proceedings of 32nd International Conference on
Acoustics,
Speech, and Signal Processing (ICASSP), Honululu, Hawai'i, pp. 397-400,
April 2007.
- Abstract:
In this paper, we present an algorithm for robustly estimating the
fundamental frequency in speech signals. Our approach is based on
pitch-scaled harmonic filtering (PSHF). Following PSHF, we perform a
filtering in the frequency domain using the short-time Fourier
transform in order to separate the harmonic and non-harmonic parts of
the processed signal. We enhance the standard PSHF approach by using a
range of window lengths and a cost function that is applied to each
window size. This cost function takes into account the energy at the
harmonic and non-harmonic frequency coefficients to estimate harmonic
energy for a frame. By using energy peaks and applying a cost function
that considers the change in pitch in subsequent frames, we then
determine the final pitch contour. We evaluated our approach on the
Keele database. As the experimental results demonstrate, our methods
performs robustly for noisy speech and has a good performance for clean
speech in comparison with state-of-the-art algorithms.
back
to selected multimodal communication and speech processing publications