H(z) =
| b0z - 2 + b1z - 1 + b2 |
| a0z - 2 + a1z - 1 + a2 |
Collection of Articles usefull in Audio and Speech Processing
Understanding the measurement of sound intensity in decibels (dB)
Sound intensity is frequently expressed in terms of decibels (dB). The decibel (1/10 of a Bel) was named in honour of Alexander Graham Bell. It expresses the logarithm to the base 10 of
the ratio between two sound intensities or (sound pressures)2.
The
internationally recognised reference standard intensity for sound is 10-12
watts per m2 which corresponds to a sound pressure of 2.10-5
N/m2 (or Pascal). For a pure tone at 1000 Hz this is close to the
threshold of hearing for young healthy adults.
style='mso-bidi-font-weight:normal'> | dB | Sound pressure (N/m2; | Relative sound |
Jet aeroplane, 80 ft from tai; hair cell damage | 120 dB | 20 | 10-6 |
Busy traffic, shouting | 80 dB | 2.10 -1 | 104 |
Conversational speech | 60 dB | 2.10 -2 | 103 |
Residential area at night | 40 dB | 2.10 -3 | 102 |
Whisper at 5ft | 20 dB | 2.10 -4 | 101 |
Threshold for hearing 1000 Hz young adult | 0 dB | 2.10 -5 | 1.0 |
An efficient method of Huffman decoding for MPEG-2 AAC and its performance analysis Jae-Sik Lee Jong-Hoon Jeong Tae-Gyu Chang This paper appears in: Speech and Audio Processing, IEEE Transactions on |
| Abstract This paper presents a new method for Huffman decoding specially designed for the MPEG-2 AAC audio. The method significantly enhances the processing efficiency of the conventional Huffman decoding realized with the ordinary binary tree search method. A data structure of one-dimensional array is newly designed based on the numerical interpretation of the incoming bit stream and its utilization for the offset oriented nodes allocation. The Huffman tree implemented with the proposed data structure allows the direct computation of the branching location, eliminating the need for the pipeline-violating "compare and jump" instructions. The experimental results show the average performance enhancement of 67% and 285%, compared to those of the conventional binary tree search method and the sequential search method, respectively. The proposed method also shows slightly better processing efficiency, while requiring much less memory space, compared even with those up-to-date efficient search methods of Hashemian and its variants. |