The dialect film "Love Letter to Grandma", which is based on the culture of the World Memory Heritage "Qiao Pi", will start in Hong Kong and Macao, Singapore, Malaysia and Brunei.

In both my native Scots language and adopted Cumbrian dialects, 'con' is squirrel (red squirrel). Squirrel is frequently seen as a trickster figure, but having it living near your home protests against malevolent beings. art: Jean-Baptiste Monge

【Member Intro: Juice=Juice 】 Day 4: Riai Matsunaga 🎤 Powerful vocals & authentic Kansai dialect! Full video on FB: Official SNS: @JuiceJuice_uf #JuiceJuice# #RiaiMatsunaga# #松永里愛# #HelloProject# #Jpop# #05Line#

AI that finally hears you. 👂 Hy ASR 3.0 preview drops today. Powered by Hy3’s language brain → precision ASR + deep semantic understanding Wins on: • general recognition • context awareness • multi-scenario robustness • dialect coverage Messy real-world audio? Clean, coherent transcripts that nail your intent. Open + internal benches: leading. Multilingual WER ≈ 3%. Voice just got an upgrade. 🔥 #HyASR# #TencentAI# #Hy3#

🌍Introducing Hy ASR 3.0 preview, a speech recognition model from @TencentHunyuan built to understand, not just transcribe What we improved: - Cleaner on real-world audio: dialects, code-switching, and long-form content with less error accumulation over time - Context-aware correction: homophones and ambiguous phrases get resolved from context, not guessed in isolation - Hotword injection: drop in brand names, people, domain terms without retraining. Lowers integration cost for niche use cases - Built for noisy rooms: whisper, background noise, tricky acoustic conditions stay stable

Over 90 per cent of people in China speak regional forms of Chinese, commonly referred to as dialects. But most of the population can still communicate using Putonghua. How did China unify its spoken language? #china# #language# #dialect# #culture# #diversity#

# Hermes Agent Features and Practical Usage 🚀 More than remembering facts, this memory continuously infers who you are from conversation. The result is an agent that understands you, getting more on-target the longer you use it. 📌 Title and Feature URL Title: Honcho Memory URL: 📝 Overview Honcho is an AI-native memory backend that goes beyond simple key-value storage. After each turn it performs "dialectic reasoning" to automatically derive insights about your preferences, communication style, goals, and behavioral patterns, building a user model that deepens over time. 🔧 How It Works ・Dialectic reasoning is multi-pass analysis: Pass 0 produces an initial assessment, Pass 1 self-audits for gaps, and Pass 2 reconciles contradictions into a final synthesis (depth 1-3). ・New users get cold-start queries probing general preferences and goals; returning users get warm-session queries prioritizing current context. ・Where built-in memory is manually curated static facts, Honcho maintains server-side profiles with automatic reasoning, enabling semantic search over conclusions and multi-agent peer isolation. ・Five tools integrate: honcho_profile (read/update peer identity cards), honcho_search (semantic search over memory and conclusions), honcho_context (retrieve session context with summaries), honcho_reasoning (synthesized reasoning at a chosen depth), and honcho_conclude (create/delete conclusions, useful for PII management). 🛠 Practical Usage ・Run `hermes memory setup honcho` for guided setup; config is written to `~/.honcho/config.json` (global) or `$HERMES_HOME/honcho.json` (per-profile). ・Key config keys: `contextCadence` (base-context refresh interval), `dialecticCadence` (LLM reasoning interval), `dialecticDepth` (multi-pass depth), `recallMode` (hybrid / context / tools), `writeFrequency` (async / turn / session), plus `apiKey` / `peerName` / `aiPeer` / `workspace`. ・In the default hybrid mode, base context and dialectic supplements inject into the system prompt automatically while tools stay available. ・Once Honcho is active, subcommands like `hermes honcho status` become available. 🎯 Use Cases ・As a long-term assistant, track a user's working preferences across months. ・Keep a coding assistant and a personal assistant talking to the same user with independent models, preventing context bleed. ・Reduce repetitive topic recaps and raise suggestion accuracy via session-scoped injection. ⚠️ Caveats ・Cost scales with reasoning depth (depth 2-3 means more LLM calls; balance via cadence settings). ・New peers need a background prewarm; if it doesn't complete in time, a bounded synchronous fallback applies. ・In recallMode, tools mode gives the agent control but needs explicit reasoning calls, while context mode hides tools and reduces flexibility. State is server-side, so migrating from file memory requires a data export. #HermesAgent# #Memory#