EDBT 2026 Demo / reviewers in the wild / expert
Chin-Chan Chang
dblp:38/7163
· DBLP profile ↗
1ranked-venue papers
0as first author
0since 2021 · last 2002
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Artificial intelligence and machine learning · 1
Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.
| Computer architecture, parallel and distributed computing, and storage systems
1 paper |
Hardware accelerators and domain-specific architectures · 44% Integrated circuit design · 44% Reconfigurable computing and FPGAs · 13% |
Topics — the 2 heaviest of 3, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Integrated circuit design
digital circuit design |
0.0 | 1 | 2002 | Chip design of portable speech memopad suitable for persons with visual disabilities · IEEE Trans. Speech Audio Process. 2002 |
Hardware accelerators and domain-specific architectures › signal processing accelerator
speech recognition accelerator |
0.0 | 1 | 2002 | Chip design of portable speech memopad suitable for persons with visual disabilities · IEEE Trans. Speech Audio Process. 2002 |
Methods — techniques the papers use, named apart from their topics
low bit-rate speech coding · 0.0line-spectrum-based interpolation · 0.0dynamic time warping · 0.0cepstrum extraction · 0.0
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2002 | Chip design of portable speech memopad suitable for persons with visual disabilitiesabstractThis paper presents the design of a speech recognition and compression chip for portable memopad devices, especially suitable for use by the visually impaired. The proposed chip design is based on several cores of which they can be regarded as intellectual property (IP) cores to be used for a variety of speech-related application systems. A cepstrum extraction core and a dynamic warping core are designed for mapping the speech recognition algorithms. In the cepstrum extraction core, a novel architecture computes the autocorrelation between the overlapping frames using two pairs of shift registers and an intelligent accumulation procedure. The architecture of the dynamic time warping core uses only a single processing element, and is based on our extensive study of the relationship among the nodes in the dynamic time warping lattice. Bit rate is the key factor affecting the memory size for speech compression; therefore, a very low bit-rate speech coder is used. The speech coder exploits a line-spectrum-based interpolation method, which yields fine quality synthesized speech despite the low 1.6 kbps bit rate. The 1.6 kbps vocoder core is cost-effective, and it integrates both encoder and decoder algorithms. The proposed design has been tested via hardware simulations on Xilinx Virtex series FPGAs and a semi-custom chip fabricated by 0.35 /spl mu/m CMOS single-poly-four-metal technology on a die size approximately 4.46/spl times/4.46 mm/sup 2/. Jhing-Fa Wang, Jia-Ching Wang, Han-Chiang Chen, Tai-Lung Chen, Chin-Chan Chang, Ming-Chi Shih |
IEEE Trans. Speech Audio Process. | 5 |