An API powered by Google's AI technology allows you to accurately convert speech into text. You can accurately caption your content, provide a better user experience with products using voice commands, and gain insight from customer interactions to improve your service. Google's deep learning neural network algorithms are the most advanced in automatic speech recognition (ASR). Speech-to-Text allows for experimentation, creation, management, and customization of custom resources. You can deploy speech recognition wherever you need it, whether it's in the cloud using the API or on-premises using Speech-to-Text O-Prem. You can customize speech recognition to translate domain-specific terms or rare words. Automated conversion of spoken numbers into addresses, years and currencies. Our user interface makes it easy to experiment with your speech audio.
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Contact center QA teams evaluate 1 to 5% of calls manually. QEval eliminates that bottleneck by applying AI speech analytics and automated scoring to 100% of interactions across voice, chat, and email, using a classification engine trained on 138M+ real conversations.
Capabilities span quality monitoring, compliance detection for PCI, HIPAA, and GDPR at 98% accuracy, sentiment analysis, keyword identification, agent coaching workflows, performance gamification, and predictive analytics across 110+ configurable dashboards. Quality scoring runs at 94% accuracy with zero manual intervention.
Deployment takes 30 days. Industry standard is 90 to 120. No disruption to live operations. Etech Global Services built QEval from two decades of running Fortune 500 contact centers in healthcare, telecom, retail, banking, and BPO. ISO 27001, SOC 2, PCI-DSS certified. Built for QA leaders and operations teams scaling coverage without adding headcount.
QEval also provides call recording management, screen capture, custom evaluation forms, calibration tools for QA consistency, root cause analysis, trend identification, and automated alert systems for compliance breaches. The voice of customer module tracks customer sentiment across touchpoints to identify service gaps and training opportunities. Real-time monitoring lets supervisors intervene during live interactions. Role-based access controls, audit trails, and data encryption ensure enterprise-grade security. QEval supports multi-site and multilingual contact center environments with centralized reporting across locations.
API integrations connect QEval with existing CRM, telephony, and workforce management systems. Automated report scheduling delivers insights to stakeholders without manual effort.
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Anam
Anam serves as a comprehensive platform for creating engaging AI avatars designed for dynamic video conversations in real-time. Each avatar is crafted from a combination of a facial appearance, vocal attributes, a language processing model, a guiding system prompt, accumulated knowledge, and various tools, enabling it to actively listen, engage, and execute tasks during live dialogues. Users have the flexibility to develop a new agent from the ground up or enhance an existing one by adding a unique face, catering to needs in customer support, sales interactions, lead qualification, language education, training sessions, onboarding processes, and front-desk medical assistance. The platform's Turnkey pipeline seamlessly manages aspects such as speech recognition, responses generated by large language models (LLMs), text-to-speech conversion, facial generation, and the delivery of content over WebRTC, while developers also have the option to integrate their own LLMs, speech recognition tools, or voice systems, or solely stream audio for facial rendering. Additionally, with Anam's CARA-4 model, every pixel is manipulated in real time, resulting in stunning photorealistic visuals, fluid head movements, subtle micro-expressions, and emotional responses that align with the conversation's tone. Moreover, the Director Notes feature empowers creators to fine-tune an avatar's performance through specific presets or detailed instructions, allowing for adjustments in expressiveness to optimize engagement. This innovative approach not only enhances user interaction but also opens new avenues for personalized communication in various fields.
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Gemini 3.8 Flash TTS
Gemini 3.8 Flash TTS is a generative text-to-speech model from Google designed for expressive voice creation, character design, dialogue direction, and multilingual audio production. Instead of limiting users to fixed voice presets, the model can create entirely new vocal identities from natural-language descriptions. Developers and creators can specify attributes such as accent, role, timbre, speaking style, pacing, and other voice characteristics across more than 100 languages and dialects. The model also offers access to more than 2,000 production-ready voices and supports voice replication from a short authorized audio sample. Performance controls allow users to direct individual lines with stage directions, pacing instructions, dialect shifts, emotional cues, and conversational backchanneling. Gemini 3.8 Flash TTS supports long-form generation while maintaining voice consistency, making it suitable for podcasts, audiobooks, localization, and other extended audio projects. Native two-speaker scene support lets users create multi-turn conversations from a single script while preserving distinct voices and natural turn-taking. Google includes consent verification, SynthID watermarking, and C2PA credentials to provide greater transparency and safeguards around generated and replicated voices. Gemini 3.8 Flash TTS can be used through Google AI Studio and the Gemini API and is intended for developers, creators, enterprises, media companies, and teams building expressive speech experiences.
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