ANONYMIZATION
PHI Anonymization
PHI anonymization is a critical process for protecting Protected Health Information from unauthorized access and misuse. It transforms healthcare data so it can no longer identify individuals, even when combined with other available data.
This ensures that sensitive patient information such as names, addresses, medical record numbers, diagnosis details, or biometric identifiers are either removed or altered to preserve privacy.
Nijta's Unique Advantage - Voiceprint Protection
Voiceprints are explicitly listed under biometric identifiers and are protected PHI under HIPAA.
They can uniquely identify individuals and must be anonymized before data is reused, shared, or stored.
This is a core feature of our platform , we detect and anonymize voiceprints automatically in audio to ensure full HIPAA compliance.
Speech-to-Text
Speech-to-Text or Automatic Speech Recognition (ASR) is the process of converting speech or audio into written text. Our advanced ASR technology is built on the robust foundation of OpenAI's Whisper, known for its exceptional performance in multilingual speech recognition. However, we've significantly enhanced its capabilities with in-house innovations, including the implementation of phonetic time-stamps. These detailed markers provide an extra layer of precision by capturing the timing of specific phonetic elements within the audio, enabling more granular analysis and synchronization.
Our ASR component supports multiple languages and has robust code-switching capabilities, as it effortlessly transcribes audio that blends various languages. Its built-in automatic language detection ensures that users do not have to manually specify the language, streamlining the workflow, while precise time-stamps allow for easy navigation and review of audio content.
Speaker Diarization
Speaker diarization is the process of identifying and segmenting individual speakers within an audio recording. It plays a crucial role in scenarios where multiple participants are involved, such as meetings, interviews, or call center conversations. By accurately distinguishing between speakers, diarization helps in creating clear, organized transcripts, improving sentiment analysis, and enhancing audio data analytics. This technology is particularly valuable for compliance, customer experience monitoring, and research purposes, where understanding who said what is essential for accurate analysis and reporting.
We are excited to unveil Monster, our new speaker diarization system, Nijta’s latest innovation in audio segmentation that redefines both accuracy and efficiency. This first release marks a major step forward in speaker diarization, offering precise segmentation, multilingual support, and robust performance on your noisy data. From medical conversations to customer service calls and teleconferences, our advanced model adapts to various acoustic conditions, ensuring high accuracy where other diarization systems fall short.
Biometric Anonymization
Biometric anonymization is the process of altering or removing unique vocal characteristics to prevent speaker re-identification while preserving the usability of the audio. Since voice carries biometric markers such as pitch, tone, and speech patterns, anonymization techniques ensure that speech data remains valuable for transcription, analytics, and AI training without compromising individual privacy. A pseudo voice with a choice of gender is created from a large random pool of speakers to completely prevent re-identification.
This feature is currently available in English and French. Additional languages could be requested for your particular use case.
Legal guarantees
The biometric anonymization solution of Nijta is legally guaranteed by the French Data Protection Authority, CNIL, on its effectiveness based on the following criteria derived from Opinion 05/2015 of the Article 29 Working Party. These factors determine whether anonymized voice data can still be traced back to an individual, influencing compliance with privacy regulations like GDPR and HIPAA.
Voice data passed through Nijta’s biometric anonymization solution cannot be re-identified using any of these methods, ensuring complete safety and compliance.
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