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Speech Recognition
5 posts about Speech Recognition. Every summary links to the original.
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Code-Switching Detection via Language-Selective Dimensions in Speech Foundation Models
Code-switching, the alternation between languages in a single utterance, is common in multilingual speech but underrepresented in training corpora for speech models. To address this, a lightweight method detects code-switching directly from speech without requiring multilingual transcriptions. The approach leverages language-selective dimensions in pretrained speech encoders by identifying hidden-state dimensions selective to each language from monolingual recordings and aggregating frame-level activations to predict code-switching. On the CS-FLEURS dataset covering 14 language pairs, the Whisper-small encoder achieves a mean F1 of 0.798, outperforming a CNN baseline (0.776) and a HuBERT linear baseline (0.751). These results show that pretrained speech encoders inherently encode the information necessary for code-switching detection, offering a scalable tool for building more representative multilingual corpora.
AI-powered agents for contact center in Australia: containment quality, not deflection
The Commonwealth Bank episode in 2025 demonstrated that a deflection metric is not a resolution metric: the bank reversed 45 redundancies after call volumes rose despite a voice bot credited with diverting 2,000 calls weekly. By May 2026, on a rebuilt platform, the same automation program achieved 84.6% end-to-end resolution for self-service messaging interactions. A peer-reviewed 2024 study found Whisper’s match error rate significantly higher for Australian English than American English, an effect of roughly 1.3 percentage points, with non-native accents worst affected. Australian regulation as of September 2026 imposes no affirmative AI disclosure duty, but misleading conduct provisions apply and an automated decision-making transparency obligation commences December 2026. Twilio’s platform offers an Australian region with emergency calling, model-agnostic agent execution, and a memory layer that preserves context during handoffs, addressing the containment quality gap.
AI-powered agents for contact center in India: what they can and cannot do
AI voice agents in Indian contact centers conduct end-to-end customer conversations using speech recognition, a language model, and text-to-speech, differing from agent assist which only suggests actions. Indian deployments are past pilot: Meesho handles 60,000 calls daily with a 75% cost reduction, and Bajaj Finance reports 71% of DIY service volumes handled by AI at one-third the human cost. The four-stage loop—speech recognition, language model, speech synthesis, telephony—must complete before the pause feels wrong, making architecture more critical than model choice. The Voice of India benchmark shows no system achieves under 20% word error rate across all 15 languages, so engine choice must be per-language and swappable. The RBI FREE-AI committee recommends informing customers they are talking to AI, human handling of complaints, and a route to a person, though these are not yet binding.
Best AI solutions for contact center in Philippines: a 2026 buyer’s guide
This guide compares AI contact center platforms for Philippine enterprises, focusing on regulatory and language constraints rather than feature lists. BSP Circular 1160 requires immediate written acknowledgement, 24/7 availability, and a dedicated fraud line, while BSP’s June 2026 AI governance principles hold institutions accountable for outsourced models. The NPC’s draft PIA circular would classify AI as high-risk, giving 90 days to comply after finalization. No independent Taglish benchmark exists, so the guide advises selecting a platform that allows swapping speech engines rather than committing to one vendor’s model. Philippine Airlines reduced wait times from two hours to under one minute and raised satisfaction from 67% to 95% using Twilio Flex.
AI-powered agents for contact center in Philippines: what the term actually means
In the Philippines, an AI-powered agent usually means a human agent assisted by AI for transcription, answer retrieval, live coaching, and wrap-up, not an autonomous software agent. The contact center sector employs 1.68 million people and earned $33.9 billion in 2025, with 56% of IBPAP members actively implementing AI. Published figures show a 22% reduction in call handling time from Concentrix and a 37% increase in agent satisfaction from TELUS Digital, but no benchmark measures Taglish speech. The IBPAP survey found 8% of operators reduced headcount, 13% increased it, and 24% saw job role shifts, while the IT-BPM sector added 70,000 net staff in 2025. Platforms like Twilio allow composable assist layers using models from OpenAI, Anthropic, or Azure, important where the language problem is unsolved and no Philippine rule requires disclosing AI use.
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