Influence of Filter Bank Structure on the Statistical Significance of Coefficients in Cepstral Analysis for Acoustic Signals

Author(s):  
Akhil Jose ◽  
Justin Joseph ◽  
Glan Devadhas ◽  
M. M. Shinu

The performance of Mel scale and Bark scale is evaluated for text-independent speaker identification system. Mel scale and Bark scale are designed according to human auditory system. The filter bank structure is defined using Mel and Bark scales for speech and speaker recognition systems to extract speaker specific speech features. In this work, performance of Mel scale and Bark scale is evaluated for text-independent speaker identification system. It is found that Bark scale centre frequencies are more effective than Mel scale centre frequencies in case of Indian dialect speaker databases. Mel scale is defined as per interpretation of pitch by human ear and Bark scale is based on critical band selectivity at which loudness becomes significantly different. The recognition rate achieved using Bark scale filter bank is 96% for AISSMSIOIT database and 95% for Marathi database.


1995 ◽  
Vol 31 (18) ◽  
pp. 1561-1562
Author(s):  
X.Q. Gao ◽  
Z.Y. He ◽  
H.X. Zhou
Keyword(s):  

2018 ◽  
Vol 54 (1) ◽  
pp. 18-20 ◽  
Author(s):  
Wenxu Zhang ◽  
Qiuying Du ◽  
Qingbo Ji ◽  
Tao Chen

2016 ◽  
Vol 40 (3) ◽  
pp. 68-82 ◽  
Author(s):  
Goktug T. Cinar ◽  
James P. Sain ◽  
Jose C. Principe

The hierarchical linear dynamical system (HLDS) is a self-organizing architecture to cluster acoustic time series. The HLDS architecture is equivalent to a Kalman filter whose top-layer state learns to create subspaces that tessellate the acoustic signal in regions that correspond to different musical pitches. The observation layer of the HLDS is built from a biologically plausible gammatone filter bank that provides the representation space for the state assignments. An important characteristic of the methodology is that it is adaptive and self-organizing, i.e., previous exposure to the acoustic input is the only requirement for learning and recognition. In this article we show that the representation space that the algorithm learns from acoustic signals preserves the organization found in monophonic notes, and exhibits (for isolated pitches and triads) properties suggested in the theory of efficient chromatic voice leading and neo-Riemannian theories.


2017 ◽  
Vol 9 (6) ◽  
pp. 1279-1291 ◽  
Author(s):  
Keiichi Motoi ◽  
Naoki Oshima ◽  
Masaki Kitsunezuka ◽  
Kazuaki Kunihiro

This paper presents a second-order tunable single-ended (unbalanced) bandpass filter (BPF) with continuous 0.4–3-GHz coverage and a tunable balun BPF with continuous 1.1–1.7-GHz coverage for software-defined radio transceivers with the use of band-switchable and radio frequency (RF)-micro-electromechanical systems (MEMS)-tuned resonators. The BPFs are realized with two pairs of RF switches for coarse-tuning and RF-MEMS-tunable capacitors for fine-tuning. On the one hand, for the tunable single-ended BPF, a transition between three bands is enabled using two pairs of RF switches. On the other hand, for the tunable balun BPF, a transition between two bands is enabled using one pair of RF switches. Furthermore, the three-band switchable single-ended BPF is constructed in a nested two-filter bank structure for expanding the tuning range without increasing the footprint. In addition, to complement the discrete band gaps, RF-MEMS capacitor-tuned resonators are used, and a continuous tuning range of nearly the entire ultra-high-frequency band is achieved. The filter bank is fabricated on a Duroid substrate with εr = 3.5 and h = 0.787 mm. The filter bank has an insertion loss of 3.2–6.8 dB and a 1-dB bandwidth of 65–450 MHz with a continuous tuning range of 0.4–3 GHz.


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