| | October 20158CIOReviewSee No Evil, Hear No Evil, Speak No Evil­Managing Audio in E-DiscoveryBy Jim Vint, MD-Legal Technology Solutions Practice and Leader of the eDiscovery Practice, Navigant Document requests involving audio recordings are becoming more prevalent, especially when the requesting party is the CFTC or the SEC. Regulation in Dodd-Frank requires corporations to retain potentially relevant oral communications such as telephone conversations, recorded meeting minutes, squawk box conversations, and both business and personal voicemail recordings. Previously, simply listening to these recordings to verify their content was sufficient to constitute a comprehensive and defensible review strategy; however, expansive data retention policies, enhanced by regulation, are making that strategy less practical in today's legal environment. In addition, identifying the speakers in each audio recording presents another challenge­who was speaking and giving instructions? Did the other speaker confirm it and who then was that confirming speaker? Was one of the key business managers under investigation on that call?Imagine you have preserved 50 terabytes of audio that now require review, attempting to listen to each recording would be cost prohibitive. The financial services industry is a great example of this. Considering squawk boxes can record 24 hours a day, 7 days a week, a corporation with 50 terabytes of audio could be facing 920,000 hours (assuming 18 audio hours per GB) of review time. This would be the equivalent of listening to the War and Peace audio book 13,000 times. In response, legal teams are looking to leverage technology to more effectively identify relevant information within audio recordings. Automatic Speech recognition ("ASR") - the translation of spoken words into text-is the technology that legal teams are turning to because it enables keyword searching and other text analytics to target potentially relevant content within audio recordings. With ASR, large teams of reviewers no longer have to sit and listen to each recording to identify relevant content. ASR is relatively new to the legal space, and while its results are not perfect, it can be used defensibly to implement keyword search when combined with a rigorous quality control sampling plan. There are two main methods of ASR that the legal community's technology applications use: phonetic searching and automatic transcription. Both can be beneficial but it is important to consider their respective strengths and weaknesses:The phonetic searching method converts an audio recording into a phonetic representation of its words. The representation is comprised of a series of phonemes-the basic units of a language's phonology. When a recording contains the same sound as a phoneme string (search term translated into its phonemes) that recording is identified as a hit. Phonetic searching generally returns results quickly and does not require a comprehensive dictionary to define the keywords and/or industry specific language. It does return false positives when the sound of the keyword is opinionin my
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