A Novel Acoustic Fingerprint Method for Audio Signal Pattern Detection
Title | A Novel Acoustic Fingerprint Method for Audio Signal Pattern Detection |
Publication Type | Conference Paper |
Year of Publication | 2014 |
Authors | Alias T, E., Naveen, N., Mathew, D. |
Conference Name | Advances in Computing and Communications (ICACC), 2014 Fourth International Conference on |
Date Published | Aug |
Keywords | Acoustic Fingerprint, acoustic fingerprint method, acoustic noise, acoustic signal detection, Acoustic signal processing, Acoustics, Audio detection, Audio recognition, audio signal pattern detection, audio signal processing, background noises, computational complexity, Correlation, efficient audio signal recognition algorithm, finite state machine, Finite State Machine(FSM), finite state machines, frequency-domain analysis, FSM model, hybrid time-frequency approach, mechanical sounds, Noise measurement, Pattern recognition, Pitch frequency, Spectral signature, speech recognition techniques, time-domain analysis, Time-frequency Analysis, Time-Frequency processing |
Abstract | This paper presents a novel and efficient audio signal recognition algorithm with limited computational complexity. As the audio recognition system will be used in real world environment where background noises are high, conventional speech recognition techniques are not directly applicable, since they have a poor performance in these environments. So here, we introduce a new audio recognition algorithm which is optimized for mechanical sounds such as car horn, telephone ring etc. This is a hybrid time-frequency approach which makes use of acoustic fingerprint for the recognition of audio signal patterns. The limited computational complexity is achieved through efficient usage of both time domain and frequency domain in two different processing phases, detection and recognition respectively. And the transition between these two phases is carried out through a finite state machine(FSM)model. Simulation results shows that the algorithm effectively recognizes audio signals within a noisy environment. |
DOI | 10.1109/ICACC.2014.21 |
Citation Key | 6905990 |
- finite state machine
- Time-Frequency processing
- Time-frequency Analysis
- time-domain analysis
- speech recognition techniques
- Spectral signature
- Pitch frequency
- Pattern recognition
- Noise measurement
- mechanical sounds
- hybrid time-frequency approach
- FSM model
- frequency-domain analysis
- finite state machines
- Finite State Machine(FSM)
- Acoustic Fingerprint
- efficient audio signal recognition algorithm
- Correlation
- computational complexity
- background noises
- audio signal processing
- audio signal pattern detection
- Audio recognition
- Audio detection
- Acoustics
- Acoustic signal processing
- acoustic signal detection
- acoustic noise
- acoustic fingerprint method