Can Text Message Be Used Against You in Court
Voice recognition has started to feature prominently in intelligence investigations. Examples abound: When ISIS released the video of journalist James Foley existence beheaded, experts from all over the world tried to place the masked terrorist known as Jihadi John by analyzing the audio of his vocalization. Documents disclosed by Edward Snowden revealed that the U.S. National Security Agency has analyzed and extracted the content of millions of phone conversations. Call centers at banks are using vox biometrics to authenticate users and to identify potential fraud.
Only is the science backside voice identification sound? Several articles in the scientific literature have warned near the quality of one of its main applications: forensic phonetic expertise in courts. We take compiled two dozens judicial cases from around the world in which forensic phonetics were controversial. Contempo figures published past INTERPOL indicate that one-half of forensic experts nevertheless use audio techniques that have been openly discredited.
For years, movies and television series like CSI paint an unrealistic picture of the "science of voices." In the 1994 movie Clear and Present Danger an expert listens to a cursory recorded utterance and declares that the speaker is "Cuban, aged 35 to 45, educated in the […] eastern Usa." The recording is then fed to a supercomputer that matches the voice to that of a suspect, concluding that the probability of right identification "is 90.1 percent." This sequence sums up a adept number of misimpressions about forensic phonetics, which have led to errors in existent-life justice. Indeed, that film scene exemplifies the and then-called "CSI effect"—the "miracle in which judges hold unrealistic expectations of the capabilities of forensic scientific discipline," says Juana Gil Fernandez, a forensic speech scientist at the Consejo Superior de Investigaciones Cientificas (Superior Quango of Scientific Investigations) in Madrid, Spain.
In 1997 the French Acoustical Society issued a public request to end the apply of forensic vox science in the courtroom. The request was a response to the case of Jerome Prieto, a man who spent x months in prison because of a controversial police investigation that erroneously identified Prieto's phonation in a telephone call challenge credit for a auto bombing. In that location are enough of troubling examples of dubious forensics and downright judicial errors, which have been documented past Hearing Voices, a scientific discipline journalism project on forensic science carried out past the authors of this article in 2022 and 2016.
It's incommunicable to know how many vox investigations are conducted each year because no state keeps a register, but Italian and British experts estimate that in their respective countries there must be hundreds per year. The process commonly involves at least one of the post-obit tasks: transcribing a recorded voice, comparing an intercepted vocalization to that of a suspect, putting the suspect's voice in a lineup of unlike voices, profiling a speaker based on dialect or linguistic communication spoken, interpreting noises or verifying the authenticity of a recording.
The recorded fragments subject to analysis can be telephone conversations, phonation post, ransom demands, hoax calls and calls to emergency or police numbers. One of the primary hurdles voice analysts have to face is the poor quality of recorded fragments. "The phone signal does not comport enough information to allow for fine-grained distinctions of speech sounds. You would need a ring twice as wide to tell certain consonants apart, such as f and south or m and n," said Andrea Paoloni, a scientist at the Ugo Bordoni Foundation and the foremost forensic phoneticist in Italy until his death in November 2015. To make things worse, recorded messages are often noisy, brusque and tin can be years or even decades old. In some cases, simulating the context of a phone call can be specially challenging. Imagine recreating a telephone call placed in a crowded movie theatre, using an old cell phone or ane made by an obscure strange brand.
In a 1994 article in the Proceedings of the ESCA Workshop on Automatic Speaker Recognition, Identification and Verification, the proficient Hermann Künzel estimated that 20 percent of the fragments analyzed by the German language federal police contained merely 20 seconds of usable vocalism. Nevertheless, many forensic experts are willing to work on audio excerpts that are of extremely depression quality. In the famous instance of George Zimmerman, the neighborhood spotter coordinator who in 2012 shot the young African American Trayvon Martin in Sanford, Fla., ane expert stated that he could extract a vocalism contour and fifty-fifty interpret the screams that could be heard in the background of an emergency call.
Unfortunately, these errors are non isolated exceptions. A survey published in June 2022 in the journal Forensic Scientific discipline International past INTERPOL, the international organization that represents the law forces of 190 countries, showed that one-half of the respondents (21 out of 44)—belonging to constabulary forces from all over the earth—employ techniques that accept long been known to have shaky scientific grounds. One example is the simplest and oldest phonation recognition method: unaided listening, leading to subjective judgement by a person with a "trained ear" or even to the opinion of victims and witnesses.
In 1992 Guy Paul Morin, a Canadian, was sentenced to life imprisonment for the rape and murder of a nine-yr-old girl. In addition to other evidence, the victim'south mother said she had recognized Morin's voice. Three years later on, a Deoxyribonucleic acid test exonerated Morin as the murderer. This kind of mistake is not surprising. In a study published in "Forensic Linguistics" in 2000, a group of volunteers who knew 1 some other listened to anonymous recordings of the voices of various members of the group. The rate of recognition was far from perfect, with a volunteer failed to recognize even his own voice.
This does not imply, however, that automated methods are always more than accurate than the homo ear. Actually, the offset instrumental technique used in forensic phonetics has been denied any scientific basis for a number of years, even though some of its variations are even so in utilise, according to the INTERPOL study. We are referring to voiceprinting, or spectrogram matching, in which a human observer compares the spectrograms of a word pronounced past the suspect with the same word pronounced past an intercepted speaker. A spectrogram is a graphic representation of the frequencies of the voice spectrum, as they modify in time while a word or sound is produced.
Voiceprinting gained notoriety with the 1962 publication of a newspaper past Lawrence K. Kersta, a scientist at Bell Labs, in the journal Nature. But in 1979, a report by the National Scientific discipline Foundation alleged that voiceprints had no scientific basis: the authors wrote that spectrograms are not very good at differentiating speakers and they are besides variable. "Spectrogram matching is a hoax, pure and simple. Comparison images is but as subjective as comparing sounds," said Paoloni. All the same, the technique nevertheless maintains a lot of credibility. In 2001, later DNA testing, David Shawn Pope of the U.South. was acquitted of aggravated sexual assault after spending fifteen years in prison. The confidence was partly based on voiceprint analysis.
Sounds Interpreted Differently
The scientific community has explicitly discredited some voice analysis techniques, but is notwithstanding far from reaching a consensus on the most effective method for identifying voices. There are two schools of idea, says Juana Gil Fernandez. "Linguists support the utilize of semi-automatic techniques that combine computerized assay and human interpretation, while engineers attribute more importance to automatic systems."
Semi-automatic techniques are still the most widely used. These methods are called "acoustic-phonetic" because they combine measurements obtained by listening (acoustic) with the output of automated sound analysis (phonetics). Experts who rely on acoustic-phonetic methods usually start by listening to the recording and transcribing it into phonetic transcription. Then they identify a number of features of the voice indicate. The high level features are linguistic: for example, a speaker's choice of words (dictionary), judgement structure (syntax), the use of filler words such every bit "um" or "like," and speech difficulties such as stuttering. The sum of these characteristics is the idiolect—a person'south specific, private manner of speaking. Other high level qualities are the and so-called suprasegmental features: vocalization quality, intonation, number of syllables per second and and so on.
Lower-level characteristics, or segmental features, mostly reverberate voice physiology, and are amend measured with specific software. One bones feature is the fundamental frequency. If the voice signal is divided into segments a few milliseconds long, each segment volition incorporate a vibration with an almost perfectly periodic waveform. The frequency of this vibration is the fundamental frequency, which corresponds to the vibration frequency of the vocal folds, and contributes to what we perceive as the timbre or tone of a specific vocalisation. The boilerplate primal frequency of an adult male person is about 100 hertz, and that of an adult female person is most 200 hertz. It can be hard to use this feature to pivot down a speaker. On the 1 hand, information technology varies very little between unlike speakers talking in the aforementioned context. On the other hand, the primal frequency of the same speaker changes dramatically when he or she is angry, or shouting to be heard over a bad telephone line.
Other segmental features commonly measured are vowel formants. When nosotros produce a vowel, the vocal tract (throat and oral crenel) behaves similar a system of moving pipes with specific resonances. The frequencies of these resonances (called the formants) can exist plotted in a graph that represents a specific "vowel space" for each speaker, and the graph tin can exist compared to that of other speakers.
In spite of its popularity, the acoustic-phonetic method raises some problems. Considering information technology is semi-automatic, it leaves margin to subjective sentence, and sometimes experts working on the aforementioned cloth using a like technique can accomplish discordant conclusions. In improver, at that place are very few data on the range and distribution in the general population of phonetic features other than the cardinal frequency. For these reasons, the nigh rigorous experts say that we can never be certain of the identity of a speaker based on voice lone. At most, we tin can say that ii voices are uniform.
Automated Systems Tin Produce False Positives
In the 1990s a new system that minimized human being judgment started to gain popularity: automatic speaker recognition. In ASR the recordings are processed by software that extracts features from the signal, categorizes them and matches them to the features in a vox databank. Nearly algorithms piece of work past dividing the point into brief time windows and extracting the corresponding spectra of frequencies. The spectra and then undergo mathematical transformations that excerpt parameters, chosen cepstral coefficients, related to the geometric shape of the vocal tract. Cepstral coefficients provide a model of the speaker's vocal tract shape. "What we do is very different from what linguists practice," says Antonio Moreno, vice president of Agnitio, the Spanish company that produces Batvox, the most widely used ASR system, according to INTERPOL. "Our organization is much more precise, is measurable and can be reproduced: two different operators volition get the same upshot from the system."
Linguists disagree. "The positive side of ARS is that it needs less human input…. The negative side is that cepstral coefficients reflect the geometry of the human vocal tract, but we are not too different from one another, and so the system tends to make false hits," says Peter French from the University of York, president of the International Association for Forensic Phonetics and Acoustics (IAFPA) and director of J.P. French Associates, the main forensic phonetics company in the U.M. "I believe that automated systems should be combined with man intervention," French says.
Other experts are more extreme in their criticism: "At the moment ASR does not have a theoretical basis stiff enough to justify its employ in existent-life cases," states Sylvia Moosmuller, an audio-visual scientist at the Austrian Academy of Sciences. One of the main reasons for skepticism is the fact that most ASR algorithms are trained and tested on a voice database from the U.S. National Found of Standards and Technology (NIST). The database is an international standard, but it includes only studio recordings of voices that neglect to estimate the complication of real life, with speakers using unlike languages, communication styles, technological channels and so on.
"In fact, what the program is modeling is not a vox, but a session, made upwards of voice, communication aqueduct and other variables," Moreno says. At the beginning, voice verification analysts tried to replicate the context in which a voice had been recorded. But near 10 years ago they changed arroyo, and instead resorted to algorithms that reduced the affect of recording weather condition, chosen compensation techniques. "In the NIST database, the same speaker is recorded through many different channels, and many dissimilar speakers are recorded through the same channel", Moreno explains. "Compensation techniques are tested on this dataset, and allow us to uncrease the speaker's characteristics from that of the session." In other words, a program trained with this method should exist able to identify the same speaker in two different phone calls, one placed past landline, for instance, and the other by cell telephone.
Moreno believes that automatic speaker identification "is more than gear up to produce valid results and improve the reliability of forensic evaluations." However, he admits that ASR "is one of the many techniques bachelor to experts, and the techniques complement each other: the more advanced labs have interdisciplinary groups."
The main problem with ASR may lie not in the software itself but in the person using information technology. "It takes a voice scientist. Y'all cannot just place any operator in front of a computer…. These programs are like airplanes: you tin purchase a airplane in one day, but you cannot learn how to fly in three weeks," says Didier Meuwly, of the Netherlands Forensic Institute. However companies sell equally much as possible, and they finish up selling software to customers who are not experts in forensic voice matching, says Geoffrey Stewart Morrison, a professor of linguistics at the Academy of Alberta, Canada. Agnitio offers a three-yr course, but so far but 20 to 25 percent of the hundreds of Batvox users have completed it. The Batvox tool tin cost upward to 100,000 Euros.
Modern Statistical Analyses Needed
Irrespective of the analysis method, forensic phonetics suffers from an fifty-fifty deeper scientific trouble. Overall, the discipline has non gone through the paradigm shift in the statistical approach to data that more than advanced techniques, such as forensic Dna testing, have already adopted: the shift to Bayesian statistics.
I case of this approach is presented by Morrison, the flag bearer of Bayesian statistics in forensic phonetics and a co-author of the INTERPOL study. "Imagine nosotros found a size 9 shoe impress at a crime scene, and we accept a suspect who wears size ix shoes. In another case we find a size 15 shoe print, and the suspect wears a size fifteen. In the second case, the show confronting the suspect is stronger, because a size 15 is less common than a size ix," says Morrison. In other words, it's non plenty to measure the similarity between two shoe prints (or two voices, or two DNA samples). Analysts too accept to have into account how typical those footprints (or voices, or Deoxyribonucleic acid) are.
For voice, the problem can be framed every bit follows: If a suspect and a criminal are the aforementioned person, how likely is the similarity between the ii voices? And if they are not the same person, how likely is the similarity? The ratio of these two probabilities is called the likelihood ratio, or strength of evidence. The higher the strength of prove (for instance, for voices that are very similar and very atypical), the stronger the evidence.
A higher or lower likelihood ratio can increase or diminish the likelihood of culpability, but the probability is besides dependent on other cues and evidence, forensic and not. As is typical of Bayesian statistics, the probability is not calculated once and for all, only is constantly adapted equally new testify is discovered.
In the guidelines for forensic science published in June 2015, the European Network of Forensic Science Institutes recommends the use of a Bayesian framework, and specially of the likelihood ratio. However, according to the INTERPOL report, only 18 of the 44 experts surveyed had made the switch.
One serious obstacle interferes with the awarding of Bayesian statistics: It is difficult to estimate how typical a voice is, because there are no statistical norms on the distribution of phonation features. "If you take a database of two million finger prints y'all can be quite confident of the reliability of your estimates, but vocalization databases are much smaller," said Paoloni. For example, the DyViS databank used in the U.K. includes 100 male speakers, virtually of them educated at Cambridge. Moreno is certain that some constabulary databanks, which are non public, comprise thousands of voices, and that some organizations have databases reaching hundreds of thousands of speakers.
"In the era of big data, the most reasonable affair to practise would be to set a corpus with a large amount of information," modeled on the platforms that provide online services, said Paoloni. Given that at that place is nothing similar, Morrison'southward recipe is to collect recordings of speakers within populations relevant for each instance, based on demographic features (gender, language, dialect and so on) and speaking style (tired, excited, sleepy) and more. The problem, nonetheless, "is that many laboratories say that they don't accept any kind of database," according to Daniel Ramos, a scientist at the Universidad Autónoma of Madrid who also collaborates with a Spanish police, the Guardia Civil.
Our investigation into the state of the art of forensic phonetics has shown some limitations of the science of voice identification, and suggests that the results of its application should exist considered with farthermost caution. "In my opinion, nobody should be condemned because of a phonation," concluded Paoloni. "In dubio pro reo--when in doubt, judge in favor of the accused. With voice, the likelihood of error is as well high for a judge to e'er be able to country that someone is guilty 'beyond any reasonable dubiety.'"
This article originally appeared in Le Scienze, and is translated and adapted with permission. It was adult with the support of Journalismfund.european union.
Further reading
INTERPOL Survey of the Use of Speaker Identification by Police force Enforcement Agencies. Morrison Thou. S., Sahito F. H., Jardine K., Djokic D., Clavet S., Berghs Due south.,Goemans Dorny C., in Forensic Scientific discipline International, Vol. 263, pp. 92-100, Junev2016. http://dx.doi.org/10.1016/j.forsciint.2016.03.044.
Forensic Speaker Recognition. Meuwly D., in Wiley Encyclopedia of Forensic Science, 2009.
Interpreting Evidence: Evaluating Forensic Scientific discipline in the Courtroom. Robertson B., Vignaux G.A., John Wiley and Sons, 1995.
The website of Hearing Voices, with cases, techniques and legislation: http://formicablu.github.io/hearingvoices/en.
Source: https://www.scientificamerican.com/article/voice-analysis-should-be-used-with-caution-in-court/
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