Multi-format speech perception hashing based on time-frequency parameter fusion of energy zero ratio and frequency band variance
Title | Multi-format speech perception hashing based on time-frequency parameter fusion of energy zero ratio and frequency band variance |
Publication Type | Conference Paper |
Year of Publication | 2019 |
Authors | Huang, Y., Wang, Y. |
Conference Name | 2019 3rd International Conference on Electronic Information Technology and Computer Engineering (EITCE) |
Date Published | Oct. 2019 |
Publisher | IEEE |
ISBN Number | 978-1-7281-3584-7 |
Keywords | cryptography, energy zero ratio, feature extraction, frequency band variance, hash sequence security, key dependence, Libraries, mean filtering, message authentication, Metrics, Microsoft Windows, multiformat speech perception hashing, perceptual hash, pubcrawl, resilience, Resiliency, Robustness, Scalability, security, sensor fusion, speech content authentication, speech processing, Speech recognition, speech signal processing, Time Frequency Analysis, Time-frequency Analysis, time-frequency features, time-frequency parameter fusion |
Abstract | In order to solve the problems of the existing speech content authentication algorithm, such as single format, ununiversal algorithm, low security, low accuracy of tamper detection and location in small-scale, a multi-format speech perception hashing based on time-frequency parameter fusion of energy zero ratio and frequency band bariance is proposed. Firstly, the algorithm preprocesses the processed speech signal and calculates the short-time logarithmic energy, zero-crossing rate and frequency band variance of each speech fragment. Then calculate the energy to zero ratio of each frame, perform time- frequency parameter fusion on time-frequency features by mean filtering, and the time-frequency parameters are constructed by difference hashing method. Finally, the hash sequence is scrambled with equal length by logistic chaotic map, so as to improve the security of the hash sequence in the transmission process. Experiments show that the proposed algorithm is robustness, discrimination and key dependent. |
URL | https://ieeexplore.ieee.org/document/9094822 |
DOI | 10.1109/EITCE47263.2019.9094822 |
Citation Key | huang_multi-format_2019 |
- resilience
- time-frequency parameter fusion
- time-frequency features
- Time-frequency Analysis
- Time Frequency Analysis
- speech signal processing
- Speech recognition
- speech processing
- speech content authentication
- sensor fusion
- security
- Scalability
- Robustness
- Resiliency
- Cryptography
- pubcrawl
- perceptual hash
- multiformat speech perception hashing
- microsoft windows
- Metrics
- message authentication
- mean filtering
- Libraries
- key dependence
- hash sequence security
- frequency band variance
- feature extraction
- energy zero ratio