LXT Launches Fully Integrated Self-Service Survey Platform Through clickworker
3-in-1 solution combines audience targeting, survey creation, and real-time reporting – with access to a global panel of 10 million contributors TORONTO, June 15, 2026 – LXT, a provider of industry-leading AI data solutions, today announced the full launch of clickworker’s self-service survey platform — a comprehensive 3-in-1 survey tool that allows businesses, researchers, and UX teams to design surveys, recruit qualified respondents, and analyze
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TTS training data for agentic AI must capture more than the sounds of a language. Tone, accent, intonation and emotional range turn a synthetic voice into a brand asset.
All data is biased. When building agentic AI, the bias in your training data should be deliberate, skewed toward the workflows your model must master, not balanced for its own sake.
Data annotation outsourcing is the practice of contracting a specialist workforce to label, generate, evaluate, or red-team the data your AI models learn from. The right partner depends on five things: workforce composition, vendor neutrality, quality metrics matched to your task type, multilingual and domain coverage, and labor diligence. Costs in 2026 range from roughly $10 an hour for commodity
Audio data collection for long-tail languages remains essential for building reliable automatic speech recognition (ASR) systems, despite recent advances in multilingual AI. While fine-tuning existing models can reduce data requirements, performance for low-resource languages still falls short of commercial expectations without high-quality transcribed audio. The bottom line: thoughtful, ethical audio data collection is not only a technical requirement but a
Synthetic voice evaluation is the process of assessing the intelligibility, naturalness and use-case appropriateness of text-to-speech (TTS) voices using controlled testing methods and carefully selected evaluators. Unlike judgments of Automatic Speech Recognition (ASR), evaluating the synthetic voice used in TTS is a relatively subjective matter, requiring variables to be carefully controlled and end goals to be clearly defined. For agentic
Computational linguistics is the scientific study of human language, examining the rules, structures and interrelated systems that humans use to communicate. While Large Language Models generate remarkably fluent text, they operate on fundamentally different principles from human language: statistical patterns between tokens rather than the layered syntactic, semantic and pragmatic structures that linguists study. Understanding this distinction is essential for