法庭语音学

本文对法庭语音学进行了研究综述,主要介绍了该学科的核心内容:说话人鉴定。在实际办案中,当未找到嫌疑人,只有犯罪分子的检材语音时,可以使用说话人画像/说话人分类技术。若没有犯罪分子的录音证据时,可以让受害人和证人进行说话人的听觉辨认。具体的辨认形式有两种:对熟人辨认和对陌生人辨认,在对陌生人辨认时可以采用语音辨认的方法进行。当检材语音和样本语音都齐备的时候,法庭语音分析专家就可以对二者进行比对检验了。目前语音比对分析涉及到的问题和领域有:基于贝叶斯方法的法庭推理和似然比计算、共振峰频率的测量应用、非解析感知与样例理论、法庭说话人自动识别以及不同方法的综合应用等。     

不同通信系统下的说话人识别探究

目的研究不同通信系统条件下,利用语音进行说话人识别的基本假设＂个体之间的语音差异大于个体自身的语音变异＂是否成立。方法选择宽带语图差异较大的不同通信系统下语音进行比对及差异的统计。结果发现说话人识别的基本假设在不同通信系统条件下成立。结论得出了不同通信系统条件下进行说话人识别的方法与判阈。     

认识非语音信息在司法话者识别中的应用

通过介绍两起利用非语音信息最终辅助确认了说话人的司法话者识别检验案件,发现在说话人识别中,当待检语音无法满足语图比对条件时,充分利用非语音信息所揭示出的个体特性将有助于解决话者识别问题。得出了当待检语音条件不充分时,依靠非语音信息来辅助进行话者识别的方法。     

正常、大声两种说话状态下语音的声学差异及对声纹鉴定的影响

本文主要通过对正常、大声两种说话状态下的普通话中三个单元音[a]、[i]、[u]的声强、时长、基频、谐波振幅差值、共振峰等声学参数的分析,综合比较了各参数的变化规律,发现大声说话时的语音并非正常语音的简单放大,二者不仅在声强上存在差别,同时在频率域上也发生了重要变化。同一人不同状态下发音的频谱特征差异性较大,同种状态下发音的相似性、可比性较强,为此,声纹鉴定中应尽量选取状态相同的语音进行比对。     

似然比在法庭说话人确认中的应用

本文把成功应用于DNA检验的证据评估方法（似然比）应用于法庭语音证据评估之中,提取语音的LPC作为识别特征,并使用45人电话对话录音中元音/a/作为样本进行了测试。结果表明该方法不仅能正确识别说话人,而且能根据当前嫌疑人样本和问题语音样本的差异,量化该语音样本作为证据的力度,为法庭提供科学合理的证据评估结果和科学解释。同时,自动特征提取的引入比起人工提取共振峰特征,提高了工作效率,识别系统性能也获得大幅提升。     

正常、大声两种说话状态下语音的声学差异及对声纹鉴定的影响

本文主要通过对正常、大声两种说话状态下的普通话中三个单元音[a]、[i]、[u]的声强、时长、基频、谐波振幅差值、共振峰等声学参数的分析,综合比较了各参数的变化规律,发现大声说话时的语音并非正常语音的简单放大,二者不仅在声强上存在差别,同时在频率域上也发生了重要变化。同一人不同状态下发音的频谱特征差异性较大,同种状态下发音的相似性、可比性较强,为此,声纹鉴定中应尽量选取状态相同的语音进行比对。     

骗亦有道

去年，湖北武汉警方在火车站郑重打出“请不要和陌生人说话”的友情提示。有学生问我对此事怎么看，我答：“对那些害怕受骗从而不和陌生人说话的人，我可以理解；对那些即使骗子再多，依然敢于和陌生人说话的人，我唯有敬意。活在这个世上，不可缺失对这个世界的基本信赖感。”     

噪声环境下的说话人识别研究

论文研究了噪声环境下的基于GMM模型和MFCC参数的说话人识别方法.白噪声环境下,说话人识别的正确率大大降低.论文研究了GMM模型在说话人识别中的应用,并采用MFCC参数作为语音的特征参数进行噪声环境下的识别研究.实验结果表明,在0dB到15dB的噪声环境下,使用GMM模型进行说话人识别时,采用MFCC参数比采用LPCC特征参数能够获得更高的识别率.在10dB的低信噪比环境下,使用MFCC参数的说话人识别,仍然可以获得75.6％的识别率,可以有效进行识别.     

降噪处理及其对语音的影响

司法声学中有两种导向的降噪处理模式：一是在语音内容辨听鉴定中。通过降噪处理，减弱噪声的掩蔽效应。提高语音听觉的清晰度和可懂度：另一种是在说话人鉴定中，通过降噪处理，减弱噪声对语音声学特征的干扰。使语图更为清晰可辨。本实验中。录制了日常生活中经常遇到的20余种噪声。通过混音，对每一个噪声合成出四个等级信噪比的含噪语音声样。然后，利用STC降噪系统、Adobe Audition软件和VS6．0语音工作站，分别对含噪语音进行降噪处理。实验发现。经过降噪处理，多数声样的噪声掩蔽效应能够减弱．部分声样的宽带语图得到改善。最后讨论了降噪处理对语音的影响及利用降噪语音进行说话人鉴定的注意事项。     

女性普通话塞音过渡音征个体特性初探

目的考察塞音过渡音征的个体特性及在说话人鉴定中的价值。方法选取9位女性发音人普通话中的6个塞音与元音/i、a、u/组成的单音节,提取每个音节F2、F3的起点值和目标值进行统计分析,并计算说话人的塞音音轨。结果 （1）过渡音征形态特征在不同说话人之间具有差异;（2）各音节的说话人区分率呈现较大区别,音节/tu/的说话人区分率较高而/khu/音节几乎不具备说话人区分能力;（3）与零声母音节相比,音节中3个元音的F2共振峰频率均值受到塞音的影响而提高,其中/i、a/F2提高的幅度要大于/u/;（4）不同说话人的音轨存在差异。结论在说话人鉴定中选取塞音音节进行比对时要注意不同音节的说话人区分率,尽量避免选取舌根塞音音节;塞音过渡音征的形态和音轨数据可以应用于说话人鉴定。     

Effects of language mismatch in automatic forensic voice comparison using deep learning embeddings

In forensic voice comparison, deep learning has become widely popular recently. It is mainly used to learn speaker representations, called embeddings or embedding vectors. Speaker embeddings are often trained using corpora mostly containing widely spoken languages. Thus, language dependency is an important factor in automatic forensic voice comparison, especially when the target language is linguistically very different from that the model is trained on. In the case of a low-resource language, developing a corpus for forensic purposes containing enough speakers to train deep learning models is costly. This study aims to investigate whether a model pre-trained on multilingual (mostly English) corpus can be used on a target low-resource language (here, Hungarian), not represented by the model. Often multiple samples are not available from the offender (unknown speaker). Samples are therefore compared pairwise with and without speaker enrollment for suspect (known) speakers. Two corpora are used that were developed especially for forensic purposes and a third that is meant for traditional speaker verification. Speaker embedding vectors are extracted by the x-vector and ECAPA-TDNN techniques. Speaker verification was evaluated in the likelihood-ratio framework. A comparison is made between the language combinations (modeling, LR calibration, and evaluation). The results were evaluated by Cllr_min and EER metrics. It was found that the model pre-trained on a different language but on a corpus with a significant number of speakers can be used on samples with language mismatch. Sample duration and speaking style also seem to affect the performance.     

A method for calculating the strength of evidence associated with an earwitness's claimed recognition of a familiar speaker

The present paper proposes and demonstrates a method for assessing strength of evidence when an earwitness claims to recognize the voice of a speaker who is familiar to them. The method calculates a Bayes factor that answers the question: What is the probability that the earwitness would claim to recognize the offender as the suspect if the offender was the suspect versus what is the probability that the earwitness would claim to recognize the offender as the suspect if the offender was not the suspect but some other speaker from the relevant population? By “claim” we mean a claim made by a cooperative earwitness not a claim made by an earwitness who is intentionally deceptive. Relevant data are derived from naïve listeners' responses to recordings of familiar speakers presented in a speaker lineup. The method is demonstrated under recording conditions that broadly reflect those of a real case.     

伪装语音的自动话者识别研究

本文以语音自动话者识别系统为平台,对实际案件中出现频率较高的10种伪装语音类型进行自动话者识别测试。通过对20位发音人的正常语音和10种类型伪装语音的话者辨认和话者确认测试,分析不同语音伪装类型对自动话者识别的影响。该结果对于深入认识伪装语音的特性及其话者识别研究具有重要意义,也为自动话者识别技术的改进提供了参考。     

辨证认识话者自动识别系统

为了警示近年来我国司法话者识别领域中出现的一些崇外、盲目追求快速与省事的苗头,结合话者自动识别系统的研究、应用状况,从语音的共性与个性、话者识别结果的相对性与绝对性出发,通过分析比对话者自动识别与语音识别所用的特征参数及实现过程,辨证分析了制约话者自动识别系统准确率的根本原因。指出了话者自动识别系统尚无法达到人们对其的期望,以及适合于司法诉讼领域的话者自动识别系统的发展方向。     

What does method validation look like for forensic voice comparison by a human expert?

Method validation has gained traction within forensic speech science. The community recognises the need to demonstrate that the analysis methods used are valid, but finding a way to do so has been more straightforward for some analysis methods than for others. This article addresses the issue of method validation for the Auditory Phonetic and Acoustic (AuPhA) approach to forensic voice comparison. Although it is possible to take inspiration from general regulatory guidance on method validation, it is clear that these cannot be transposed on to all forensic analysis methods with the same degree of success. Particularly with respect to an analysis method like AuPhA, and in a field of the size and characteristics of forensic speech science, a bespoke approach to method validation is required. In this article we address the discussions that have been taking place around method validation, and illustrate one possible solution to demonstrating the validity of voice comparison by a human expert using the AuPhA method. In doing so we consider the constraints placed on sole practitioners, which generally go unacknowledged.     

Speech Watermarking: An Approach for the Forensic Analysis of Digital Telephonic Recordings*

Abstract: In this article, the authors discuss the problem of forensic authentication of digital audio recordings. Although forensic audio has been addressed in several articles, the existing approaches are focused on analog magnetic recordings, which are less prevalent because of the large amount of digital recorders available on the market (optical, solid state, hard disks, etc.). An approach based on digital signal processing that consists of spread spectrum techniques for speech watermarking is presented. This approach presents the advantage that the authentication is based on the signal itself rather than the recording format. Thus, it is valid for usual recording devices in police‐controlled telephone intercepts. In addition, our proposal allows for the introduction of relevant information such as the recording date and time and all the relevant data (this is not always possible with classical systems). Our experimental results reveal that the speech watermarking procedure does not interfere in a significant way with the posterior forensic speaker identification.     

论声纹鉴定意见的表述形式

本文针对目前国内外讨论比较热烈的声纹鉴定意见表述问题进行了评述.首先介绍了实践中正在使用的听觉分析法、声谱比对分析法、声学分析法、听觉-声学分析法和说话人自动识别五种鉴定方法,指出了各种方法的优缺点;然后对现存的二元判决、可能性等级、似然比和英国立场声明四种鉴定意见表述形式进行了介绍和评析,通过分析发现,上述四种意见表述形式都存在一定的问题,实践中选择何种形式表述鉴定意见要综合考虑其科学性、逻辑性、现实性和可行性等多种价值选项;最后认为解决该问题的根本方法是各相关领域的专家应加强在鉴定方法上的合作性的基础研究.     

从话者识别角度认识山西汾城方言的紧喉音节

目的明确山西汾城方言紧喉音节与对应普通话音节在司法话者识别时的可比性及该紧喉音的声学特性。方法利用VS-99语音工作站对山西汾城方言紧喉音节及对应普通话音节的韵律特性、音质特性等声学特性进行定性与定量分析。结果得出了汾城方言紧喉音的发声态主要为嘎裂声,汾城方言紧喉音对声母没有明显影响,紧喉音韵母与普通话韵母在共振峰频率上的一致性要远高于共振峰相对强度上的一致性等认识。结论为在汾城方言与普通话之间进行司法话者识别以及田野调查提供了依据。