TGTGInsighttelegram intelligenceLIVE / telegram public index
← IT news | Tg Bots

TGINSIGHT SIMILAR POSTS

유사한 콘텐츠 찾기

소스 채널 @phpdevelopersuz · Post #2990 · 12월 31일

Bot API was updated to version 6.4 Forums • Bots can now open, close, edit and toggle the visibility of the General Topic. • Added support for new service messages, like ForumTopicEdited, GeneralForumTopicHidden and more. • The method sendChatAction can now send actions to any thread or topic via the message_thread_id parameter. Spoilers • Added spoiler detection via the new has_media_spoiler field in the Message class. • Bots can send media covered by a spoiler animation via the has_spoiler field in sendPhoto, sendVideo and sendAnimation. Web Apps • Added a native QR scanner popup, controllable via showScanQrPopup and closeScanQrPopup. • Web Apps launched from the attachment menu can request clipboard text via readTextFromClipboard. • Added a platform field, showing which platform the web app is being used on. General • Added the is_persistent field, to keep ReplyKeyboards open by default. See the full changelog for details on the official website. #update#BotAPI https://t.me/+VMLgtEPNL49jZmNh

결과

3개의 유사한 게시물이 발견되었습니다

검색: #sounds

当前筛选 #sounds清除筛选
Interesting Planet 🌍

@interesting_planet_facts · Post #1053 · 2025. 11. 19. PM 06:11

🌎 In 1977, the Soviet Venera 14 probe recorded mysterious low-frequency “thunder”-like sounds on Venus. Scientists now attribute these to seismic activity or wind interacting with the planet’s dense atmosphere. Venus’s surface winds move slowly, but thick air carries sound much farther than on Earth. ✨ #Venus⚡#sounds⚡#space 👉subscribe Interesting Planet 👉more Channels ​

djangoproject

@djangoproject · Post #255 · 2017. 02. 02. PM 06:57

https://github.com/tyiannak/pyAudioAnalysis #pyAudioAnalysis is a Python library covering a wide range of audio analysis tasks. Through pyAudioAnalysis you can: Extract #audio features and representations (e.g. mfccs, spectrogram, chromagram) Classify unknown #sounds Train, parameter tune and evaluate classifiers of audio segments Detect audio events and exclude silence periods from long recordings Perform supervised segmentation (joint segmentation - classification) Perform unsupervised segmentation (e.g. speaker diarization) Extract audio thumbnails Train and use audio regression models (example application: emotion recognition) Apply dimensionality reduction to visualize audio data and content similarities