📖 英文と日本語訳（一文ずつ）

🎧 通し読み（全文）

リスニング・シャドーイング用の全文です。

On May 7, 2026, OpenAI announced that it will add three new voice models to its developer API. Three models are being introduced: "GPT-Realtime-2," the first voice model featuring GPT-5 level reasoning capabilities; "GPT-Realtime-Translate," which performs real-time translation from over 70 input languages into 13 output languages; and "GPT-Realtime-Whisper," a streaming speech recognition model that provides live transcription following the speaker’s speech. The core GPT-Realtime-2 is designed to infer requests while maintaining a conversation, call tools, handle corrections and interruptions, and provide contextually appropriate responses. Specific features include a mechanism for inserting short preambles such as "Please wait a moment" before responding, a function to invoke multiple tools in parallel with audible transparency regarding their operations, and a recovery feature that naturally communicates messages like "It is taking a little longer to respond" instead of remaining silent during processing delays or failures. The context window has been expanded from the previous 32K to 128K, supporting longer, more coherent sessions and complex task flows. Furthermore, the accuracy of preserving technical terms, proper nouns, and medical terminology has improved, and the controllability of tone has also been enhanced. Users can select from five levels of reasoning depth—Minimum, Low, Medium, High, and Maximum—with the default set to Low. In performance evaluations, it outperformed GPT-Realtime-1.5 by 15.2% on Big Bench Audio, which measures audio intelligence, and showed a 13.8% improvement on Audio MultiChallenge, which measures conversational instruction-following. GPT-Realtime-Translate enables the creation of multilingual audio experiences where each speaker can communicate in their preferred language while receiving real-time translated audio and transcriptions. It is expected to be utilized in areas such as customer support, cross-border sales, education, events, and media. Vimeo has released a demo that translates product introduction videos into multiple languages during playback, while Deutsche Telekom is proceeding with verification for its use in multilingual customer support. GPT-Realtime-Whisper is a model specialized in low-latency speech-to-text conversion. It can be used for generating subtitles for meetings, lectures, broadcasts, and events, as well as for creating meeting minutes and developing voice agents that continuously understand user speech. Furthermore, it can be utilized to accelerate downstream workflows in high-frequency voice-based operations such as customer support, healthcare, sales, and recruitment. OpenAI has identified three patterns for developer-built voice experiences: "voice-to-action," which involves reasoning through user requests and executing them via tools; "systems-to-voice," which proactively provides guidance based on system context; and "voice-to-voice," which maintains conversation continuity across different languages and contexts. Zillow is developing a voice assistant capable of responding to instructions such as "find a property on a low-traffic street within my BuyAbility range and book a Saturday viewing," while companies including Priceline, Intercom, Glean, and Foundation Health are also moving forward with its implementation. Josh Weisberg of Zillow stated that prompt optimization improved call success rates from 69% to 95%—a 26-percentage-point increase—on the most challenging adversarial benchmarks. In terms of safety, the Realtime API features a built-in classifier that detects harmful content and terminates conversations, while developers can implement their own guardrails via the Agents SDK. EU data residency is also supported. Pricing for GPT-Realtime-2 is set at $32 per 1 million tokens for audio input ($0.40 for cached input) and $64 per 1 million tokens for audio output. GPT-Realtime-Translate is priced at $0.034 per minute, and GPT-Realtime-Whisper is set at $0.017 per minute. All three models are available via the Realtime API, with support for trials in the Playground and implementation through Codex.

📝 学習のヒント

1. 1まず英文を読む — 知らない単語にあたりをつけてから音声へ。
2. 2一文ずつ確認 — 日本語訳と照合し、構文を理解する。
3. 3通し読み Normal で耳を作る — 内容を追いながらリピート。
4. 4Fast でシャドーイング — 口を慣らし、リスニング速度を上げる。
5. 5翌日に復習 — 1日空けて再聴すると長期記憶に定着しやすい。