In this toolkit, the estimated signals are decomposed via a complex, auditory-motivated algorithm as [51] ŝ n ( t ) - s n ( t ) = e target ( t ) + e interf ( t ) + e artif ( t ), (29).
Here, we used a visual-to-auditory sensory substitution algorithm (SSA) to manipulate the information conveyed by sensory inputs while keeping the stimuli intact.
This was enabled by using a visual-to-auditory sensory substitution algorithm (SSA), The vOICe (Meijer 1992), which was developed as a rehabilitation tool for the blind.
Based on the existing alternative pitch algorithms for simulating the perception of the auditory system and simplified algorithms for practical applications in the areas of music and speech, the applicable algorithms have been determined, considering common types of sound in everyday soundscapes.
Good results were obtained when combining the SE algorithm with auditory modulation features and BN processing for SGMM-HMM, as well as the modified auditory modulation features for DNN-HMM.
Second, we adapt this algorithm to the auditory model output in a channel-wise manner.
Musical Stairs is composed of two foot-mounted inertial sensors, a step detection algorithm, and an auditory feedback response.
Based on wavelet moment and synchronization code, we propose a new digital audio watermarking algorithm with good auditory quality and reasonable resistance against most attacks in this paper.
Finally, taking into consideration algorithm complexity and auditory quality, we set the number of hidden states as 16 and required each GMM to have 32 mixtures and full covariance matrices in the HMM-based reference method.
Based on pseudo-Zernike moment and synchronization code, we propose a new digital audio watermarking algorithm with good auditory quality and reasonable resistance toward desynchronization attacks in this paper.
