Cross-platform, text-independent, language-agnostic speaker recognition with a seamless enrollment process, readily available to all developers
Eagle Speaker Recognition is speaker verification and identification software that distinguishes individuals using their unique voice characteristics.
Eagle Speaker Recognition, powered by deep learning, enables developers to determine “who is speaking” on any platform with no language or passphrase limitations.
# Speaker Enrollmento = pveagle.create_profiler(access_key)while percentage < 100:percentage, feedback = o.enroll(get_next_enroll_audio_data())speaker_profile = o.export()# Speaker Recognitioneagle = pveagle.create_recognizer(access_key,speaker_profile)while True:scores = eagle.process(get_next_audio_frame())
Eagle Speaker Recognition is the only readily available production-grade, highly accurate, resource-efficient, cross-platform, text-independent, and language-agnostic engine with a seamless enrollment process.
Get to know users, personalize experiences, and build trust.
Make the enrollment process seamless and natural instead of forcing a long, separate process or specific passphrases. It takes just a few seconds, try now!
Compare Detection Accuracy and Detection Error Rate of Speaker Recognition engines using open-source benchmarks. Eagle outperforms SpeechBrain, pyannote, and WeSpeaker at detecting speakers.
Eagle Speaker Recognition achieves higher detection accuracy using hundreds of times less compute and memory, returning fast results across platforms.
Recognize speakers instantly with high accuracy across the world with language-agnostic and text-independent Eagle Speaker Recognition.
Offer the same experience across all channels, including the web and mobile. Embed speaker recognition into your product without worrying about future expansions.
Start verifying and identifying users with Eagle Speaker Recognition in less than 10 minutes.
Start NowSpeaker Recognition deals with speaker identification and verification using distinguishable voice characteristics. It focuses on “who” rather than “what”.
Speaker Identification, also known as Speaker Search or Speaker Spotting, is a special application of speaker recognition that determines the identity of an unknown speaker by comparing their characteristics with the voice characteristics of known speakers.
Speaker Verification, also known as Voice Biometrics, Voice Authentication, and Voiceprinting is a subset of speaker recognition that focuses on verifying individuals’ identities using unique voice patterns.
Speaker Identification and Speaker Verification are both subsets of Speaker Recognition. If a Speaker Recognition engine does a one-to-one match to verify the claimed identity, it’s called Speaker Verification. If it does a one-to-many match, i.e., determines the speaker’s identity within a group of enrolled speakers, it’s called Speaker Identification.
The best speaker recognition engine varies among enterprises, depending on their priorities and needs. Performance, Platform Support, Scalability, Compliance, Ease of Use, Developer-Friendliness, Availability of Support, and the Total Cost of Ownership are the most important factors to consider before a decision.
Picovoice researchers published an open-source speaker recognition benchmark to give developers a head-start with evals. You can reproduce it or use your test data. If you’re not familiar with the most used metrics in speaker recognition performance evals, check out the speaker recognition performance measurement and comparison guide.
Picovoice docs, blog, Medium posts, and GitHub are great resources to learn about voice AI, Picovoice technology, and how to detect who is speaking. You can report bugs and issues on GitHub. If you need help with developing your product, you can purchase the optional Support Add-on or upgrade your account to the Developer Plan.