听觉识别符可通过相互敲击移动设备产生。
An audio identifier may be produced by tapping the mobile devices together.
AI(即听觉识别)是同VI并列的CI构成体系中不可或缺的一个组成部分。目前AI事实上是处于一种弱势地位和不被重视的处境。
AI (that is, audio identity) is tied with the VI system, which has constituted an integral part of the CI. AI is currently in a vulnerable position and the situation is not taken seriously.
文章针对该问题，探讨了AI的概念、功能及价值，分析了目前听觉识别系统的运作现状及地位，探究了AI的可行性和未来发展趋势，并就如何恰当地运用AI系统作了阐述。
For the problem, the article made a research of the concept, the function and the value of AI, take an analysis of the system to identify the status quo and the status of AI.
他们发现，所有参加者使用两种方法都获得了识别视觉和听觉刺激的能力（原文有误，above-chance指该结果有统计意思，不应置于ability之前，参见法语原文第五段最后一句话——译者注）。
They found that all the participants had acquired an above-chance ability to recognize the visual and auditory stimuli using the two methods.
利用听觉频率非线性特性的美尔倒谱作为语音识别的特征参数，来辨识说话人提供的输入口令。
Also, since MFCC represent hearing frequency nonlinear characteristic, we utilize MFCC to be another speak recognition characteristic parameter to distinguish the input passwords.
这对于人机自然交互，听觉视觉双模态语音识别，计算机视觉的研究都有重要意义。
It is important for the study of man machine natural interaction, audiovisual bimodal speech recognition and computer vision.
选用美尔倒谱系数及其差分作为语音识别的特征参数，来描述人耳的听觉频率非线性特性。
Selected for use MFCC and the difference and divided the characteristic parameter as phonetic recognition, to describe the non-linear characteristic of frequency of sense of hearing of ears of people.
利用被动声纳目标辐射噪声特征主要集中在低频部分的特点，结合听觉系统识别声音信号的原理，提出了一种被动声纳目标临界频带频谱能量的特征提取方法。
By studying the principle of hearing system in identification of sound signal, a method of feature extraction for passive sonar target based on critical band spectrum energy is proposed.
听觉研究面临的一个重要问题是在嘈杂混响环境下听者是如何识别目标声源的。
How listeners are able to detect and identify individual sound sources in noisy, reverberant environments is one of the most intriguing questions in auditory perception.
语音识别研究的根本目的是研究出一种具有听觉功能的机器，能直接接受人的口述命令并做出相应的正确的反应。
The research goal of speech recognition is to invent a kind of machine which has the function of hearing and can give correct response directly according to people's oral order.
听觉滤波器在理解听觉形成机制、听觉系统建模、语音压缩和语音识别等很多方面都有着很重要的应用。
Auditory filter plays an important role in understanding the mechanism of hearing, auditory modeling, speech compression and recognition.
实验结果说明基于视觉和听觉的多模态识别算法能提高计算机对人的情感识别率。
The findings show that the audio and video information can be combined using a rule-based system to improve the recognition rate.
但语音识别系统忽略语言的视觉特性，仅仅利用听觉特性，使得语音识别系统在噪声环境下，识别率大大下降。
However, audio-recognition system only USES the audio information of speech, and ignores the visual features of it. Under the noise circumstance, the recognition rate declines so much.
通过对听觉谱和L PC倒谱对比分析，得到了听觉谱适宜用作语音识别并具有良好的噪声鲁棒性的结论。
The spectrum of auditory model and LPC-CEP shows that this auditory model not only represents speech signal well, but also is noise robust.
通过对听觉谱和L PC倒谱对比分析，得到了听觉谱适宜用作语音识别并具有良好的噪声鲁棒性的结论。
The spectrum of auditory model and LPC-CEP shows that this auditory model not only represents speech signal well, but also is noise robust.
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