'language' 검색 결과

Multilingual communication, translation, localization, and language quality skill for translating, rewriting, localizing, summarizing, tone-matching, and reviewing content across languages. Use for multi-language prompts, UI strings, documentation, cultural adaptation, terminology consistency, bilingual output, language detection, and Indonesian/English or other cross-language workflows.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Reverse engineers malware written in less-common compiled languages (Nim, Crystal, V, Zig, D) by detecting language-specific runtime signatures, name-mangling, and runtime strings to orient analysis. Activates for requests to reverse Nim malware, identify the source language of an exotic binary, or analyze Crystal/V/Zig/D compiled samples.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Tokenize, tag, and analyze natural language text using Apple's NaturalLanguage framework and translate between languages with the Translation framework. Use when adding language identification, sentiment analysis, named entity recognition, part-of-speech tagging, text embeddings, or in-app translation to iOS/macOS/visionOS apps.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Add an AI assistant to an existing web app so users can operate its interface with everyday instructions. Covers embedding the panel, connecting a language model, testing interactions, and protecting API keys in production.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Add natural-language controls to a business dashboard
• Introduce an AI assistant into a legacy web app
• Build guided product demos using the actual interface

Inspect a codebase with pygount to measure code lines, file counts, language composition, and comment ratios. Exclude dependency folders, focus on selected languages, and get summaries or file-level results for understanding project size.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Measuring a project's code size
• Checking language composition and file counts
• Comparing code and comment ratios

Describe browser actions in everyday language and let page-agent carry them out. Useful when page elements are hard to identify reliably, with a fallback to direct element-based browser tools if the natural-language setup is unavailable.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Clicking a button described in everyday language
• Entering a search term and submitting the form
• Interacting with pages whose element identifiers change

Review page language attributes so HTML and XML readers receive consistent language information. Check matching lang and xml:lang values, validate language codes, and recommend keeping both attributes for XHTML or removing the unnecessary XML attribute from standard HTML5.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Checking language attributes in XHTML documents
• Removing unnecessary xml:lang attributes from HTML5
• Investigating incorrect screen reader pronunciation

Check and fix hreflang tags, which identify language and regional versions of web pages for search engines. Review rendered HTML and HTTP responses to find missing reciprocal links, incorrect language codes, and fallback settings.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Auditing language and regional page settings
• Checking reciprocal links between language versions
• Reviewing fallback page settings

Translate and dub existing videos with HeyGen to create versions in multiple languages. Preserve the speaker’s voice characteristics, match lip movements to translated speech, or choose audio-only translation without adjusting the video’s lip movements.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Create multilingual versions of a product demo
• Dub videos with matching lip movements
• Translate audio without changing lip movements

Build text translation into Python applications with Azure AI Translator. Covers translation into multiple languages, language detection, transliteration to another writing system, dictionary entries, usage examples, and asynchronous requests for handling larger workloads.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Add multilingual text translation to a Python app
• Detect the language of incoming text
• Convert text between writing systems

Add Azure text and document translation to TypeScript applications. Includes examples for translating into multiple languages, detecting source languages, converting writing systems, submitting document batches, and checking translation progress and supported file formats.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Translate text into multiple languages in a TypeScript app
• Detect a text's language or convert its writing system
• Translate a single document and save the result

Create multilingual voice-over audio from scripts supplied for each language using the paid Beatra service. Guides voice selection for each market, pronunciation and timing pilots, and delivery organized by language and segment for review.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Produce voice-overs from scripts prepared for each language
• Choose voices suited to each target market
• Review pronunciation and timing with pilot audio

Translate an English MkDocs documentation set into a chosen language while preserving folder structure and Markdown formatting. Update shared content references, navigation labels, notice labels, and language configuration, and check that every source file has been translated.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Add another language to English MkDocs documentation
• Translate shared content alongside documentation pages
• Update multilingual navigation and notice labels

Build text tokenizers that split multilingual text into small units for AI models. Learn how to train SentencePiece on raw text, configure BPE or Unigram splitting methods, and convert text to token IDs and back.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Preparing Japanese, Chinese, or Korean text for AI models
• Training a custom vocabulary from raw text
• Choosing between BPE and Unigram

Build image captioning, visual question answering, and text-based image search with BLIP-2. The skill explains model selection, batch processing, and memory-saving settings, with Python examples for connecting image understanding to language models.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Generating captions for multiple images
• Building a question-answering system for images
• Searching an image collection with text

Maintain the Repomix documentation website by editing guides, navigation, and search labels across languages. Follow its VitePress file structure to add a language and keep translations aligned with the English source.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Updating the Japanese installation guide
• Changing navigation and sidebar labels
• Adding a new language to the documentation

Add user-facing text to Handsontable through its translation system. The skill covers translation keys, language files, plural forms, right-to-left layouts, preserving Japanese and other East Asian input behavior, and converting text to lowercase according to language rules.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Adding translated menu labels
• Adding a language file or plural forms
• Checking Arabic or Persian right-to-left layouts

Turn plain-language requests into Cloud Logging queries for Google Cloud. Generate service-specific filters to find errors, investigate issues, or review audit logs using LQL, the language used to search these logs.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Finding recent error logs
• Filtering logs for a specific Google Cloud service
• Investigating who changed or accessed a resource

Creates target-language speech from SRT subtitle files using KrillinAI CLI, with optional dubbed video output. Covers voice selection, choosing the target lines in bilingual subtitles, and checking the generated audio and video files.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Creating narration from translated SRT subtitles
• Generating a dubbed version of an existing video
• Reading only the target language in bilingual subtitles

Guides image classification and search with OpenAI's CLIP by comparing images with text descriptions, without additional training. Includes batch processing, image-text matching, and category-based checks for potentially inappropriate images.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Classify images using text labels without additional training
• Search an image collection with natural-language descriptions
• Compare how closely images match text descriptions

Build text tokenizers, which split text into units for AI models, directly from raw multilingual text. Learn custom vocabularies with BPE or Unigram, convert text to pieces or numeric IDs, and decode the results.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Preparing text for multilingual AI models
• Training a vocabulary from Japanese text
• Reusing a tokenizer for reproducible text splitting

Create a translated copy of a Canva design by replacing text across all pages in the requested language. Keep the original intact, preserve formatting cues, and review a preview before approving the translated design for saving.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Creating a French version of a sale poster
• Translating text across a multipage Canva design
• Making another language version while keeping the original

Install language servers (gopls, typescript-language-server, pyright, rust-analyzer) and their prerequisite toolchains (Go, Node/npm, rustup) so the lsp tool works. Use when the user asks to enable or install LSP / language-server support, when lsp_enable reports a missing toolchain, or when the lsp tool reports no language server is installed.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Implement Conversational Language Understanding (CLU) using the azure-ai-language-conversations Python SDK. Use when working with ConversationAnalysisClient to analyze conversation intent and entities, building NLP features, or integrating language understanding into applications.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.