New Results on Single-Channel Speech Separation Using Sinusoidal Modeling
نویسندگان
چکیده
منابع مشابه
Speaker Independent Single Channel Source Separation using Sinusoidal Features
Model-based approaches to achieve Single Channel Source Separation (SCSS) have been reasonably successful at separating two sources. However, most of the currently used model-based approaches require pre-trained speaker specific models in order to perform the separation. Often, insufficient or no prior training data may be available to develop such speaker specific models, necessitating the use...
متن کاملSingle Channel Speech Separation Using Factorial Dynamics
Human listeners have the extraordinary ability to hear and recognize speech even when more than one person is talking. Their machine counterparts have historically been unable to compete with this ability, until now. We present a modelbased system that performs on par with humans in the task of separating speech of two talkers from a single-channel recording. Remarkably, the system surpasses hu...
متن کاملSingle Channel Speaker Segregation using Sinusoidal Residual Modeling
In this paper we address the two speaker segregation problem in a single channel paradigm using sinusoidal residual modeling. An appropriate selection of the number of sine waves, window length and hysteresis threshold, is done so as to model and synthesize the underlying signal corresponding to the speaker with the lower pitch period, using an amplitude only sine wave synthesis. The sinusoidal...
متن کاملSinusoidal Approach for the Single-Channel Speech Separation and Recognition Challenge
Most of the single-channel speech separation (SCSS) systems use the short-time Fourier transform as their parametric features. Recent studies have shown that employing sinusoidal features for the SCSS application results in a high perceived speech quality. In this paper, we make a systematic study on automatic speech recognition results for a SCSS system that uses sinusoidal features composed o...
متن کاملSource-Filter-Based Single-Channel Speech Separation Using Pitch Information
In this paper, we investigate the source–filter-based approach for single-channel speech separation. We incorporate source-driven aspects by multi-pitch estimation in the model-driven method. For multi-pitch estimation, the factorial HMM is utilized. For modeling the vocal tract filters either vector quantization (VQ) or non-negative matrix factorization are considered. For both methods, the fi...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: IEEE Transactions on Audio, Speech, and Language Processing
سال: 2011
ISSN: 1558-7916,1558-7924
DOI: 10.1109/tasl.2010.2089520