Music — a classification, not a measurement. An on-box language model (Qwen3.6-35B-A3B-FP8, prompt version 1) read this channel’s own recent posts on 13 September 2026 and assigned it the closest of 31 fixed categories, at 53% confidence. This is a model’s judgement about what the channel is likely to be about, not a fact this register measured the way a subscriber count or a view count is measured — it can be revised on a later pass, and it carries no weight anywhere else on this page. How this classification works, and why it has no browse page of its own yet.
Growth
12 measurements spanning 42 days, net -1. Dots are measurements; the straight line between them is drawn to join them, not to claim we know the path taken in between — snapshots are recorded only when a count changes, so gaps mean “no change observed”, never “interpolated”. The vertical axis spans 5,297–5,308 and does not start at zero.
Measurement log — every subscribers count we have recorded
Measured (UTC)
Subscribers
Change
17 Sept 2026, 12:15
5,298
-5
9 Sept 2026, 22:19
5,303
-4
4 Sept 2026, 09:54
5,307
+1
31 Aug 2026, 20:04
5,306
-1
28 Aug 2026, 16:05
5,307
+2
25 Aug 2026, 22:24
5,305
-1
19 Aug 2026, 16:06
5,306
+1
16 Aug 2026, 18:56
5,305
-2
13 Aug 2026, 04:56
5,307
+3
9 Aug 2026, 18:12
5,304
+4
6 Aug 2026, 23:11
5,300
+1
6 Aug 2026, 19:46
5,299
first reading
Engagement
18 posts held, back to 10 July 2026 — the reader has not yet reached the start of this channel’s public history, so older posts may sit further back, unread. Read across 8 pages of Telegram’s post history, 20 posts per page.
Nothing published in the last 30 days. ERR and ER are rolling 30-day measures, so there is nothing to compute — we hold 18 posts for this entry, the most recent from 11 August 2026. An engagement rate over an empty window would be a number about nothing.
What this channel posts
Video runtime
12m 34s
Average length
1m 15s
Measured directly from 10 videos with a duration reading, out of the posts we hold for this channel — not this channel’s whole posting history, only the sample this register has actually read. An exact reading to the second, taken from the post itself rather than from Telegram’s own rounded chrome, so it carries no ≈ mark.
Reaction mix
450 reactions across 18 posts, in 10 distinct kinds. The most used accounts for 36.0% of them.
Every reaction kind recorded on the sample, most used first
Reaction
Count
Share
Share, drawn
🔥
162
36.0%
❤
154
34.2%
👍
94
20.9%
custom 5334777864749337114
10
2.22%
🙏
9
2.00%
👏
8
1.78%
❤🔥
5
1.11%
💯
4
0.889%
👌
3
0.667%
🥴
1
0.222%
Custom emoji. One row above is a Telegram custom emoji, which the public preview renders as an element carrying only a numeric id — no character, and no image we can reach. The id is printed as-is rather than substituted with a look-alike glyph, because a stand-in would be our invention showing where a measurement should be. The count beside it is Telegram’s.
No sentiment is inferred, and none should be read in. This table is ordered by count and by nothing else. Emoji do not carry stable meaning across languages or communities — 🙏 is thanks in one channel and mourning in another — so we publish which ones were pressed and how often, and pass no judgement on what an audience meant by them.
Precision. Telegram publishes reaction counts per emoji and short-forms each one — 4.34K, 1.2M — so any single kind at or above 1,000 reaches us at three significant figures, and only counts below 1,000 are exact. The shares above are ratios of those figures and carry the same error. This is also why the total here can differ slightly from a reaction total printed elsewhere on the page: both are sums of the same rounded parts, taken over samples with different edges.
Coverage. Reactions were read on 18 of the 18 sampled posts in this sample. Summed by Telegram’s own count on each post — not by adding up the per-emoji breakdown above — those same posts carry 450 reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.
Measured over the 18 most recent posts we hold, published 10 July 2026 to 11 August 2026, using the newest reading held for each. Telegram Stars are excluded: they are a payment, not a reaction, and they have their own section.
Telegram Stars
Stars received
1
across the posts below
Posts paid on
1
of 18 we hold a reading for · 6%
Most on one post
1
single highest reading
A paid reaction is a reader spending Telegram Stars — bought with money — on a post by @resonance_music_academy. Telegram publishes the count on the public post preview alongside ordinary reactions, and this register reads it there. It is the only figure on this site that measures money moving rather than attention.
Stars are not reactions, and the two are never added. They are rendered in the same strip on Telegram and counted in the same shape, but one is a tap and the other is a purchase. The reaction totals and the engagement rate elsewhere on this page exclude every figure in this section, and no rate here is computed against a reaction count.
This is not revenue, and we publish no currency figure. What a Star costs a reader and what it pays a channel are different numbers, Telegram takes a share we cannot observe, and the terms have changed. Converting a Star count into money would be an estimate dressed as a measurement, so the count is where we stop.
Counted over the 18 most recent posts we hold for this entry, published 10 July 2026 to 11 August 2026. Star counts above 1,000 reach us in Telegram’s short form and carry the same three-significant-figure rounding as everything else on this page.
🎛 Огромная часть музыки, которую мы слушаем, сделана людьми без музыкального образования.
И правда: чтобы писать свою музыку, важнее чувствовать какого эффекта хочешь добиться. Теория просто сокращает путь: вместо перебора нот вы сразу знаете, что даст нужный результат.
Например:
Поднять шестую ступень в миноре, и он перестаёт быть грустным: появляется дорийский лад, на котором часто строятся фанк и джаз.
Сыграть т…
Нам часто пишут: «Мне 28», «Мне 32», «Мне 35». Уже поздно начинать?
Но поздно для чего? Чаще всего за словом «поздно» стоит не возраст, а страх потратить время и не получить быстрый результат. Но музыка редко работает по такому сценарию.
Многие начинают уже во взрослом возрасте — когда есть работа, обязанности и осознанное желание заниматься тем, что действительно нравится. И это точно не делает путь менее настоящи…
Как делать параллельную обработку?
Используйте дорожки Send/Return.
Send/Return нужен, когда один и тот же эффект должен работать сразу на нескольких дорожках. Вместо того чтобы добавлять ревербератор или дилэй на каждый инструмент, достаточно создать одну Return-дорожку и отправить на неё нужное количество сигнала с помощью ручки Send.
В результате одновременно звучит исходный (сухой) сигнал и его обработанная ве…
Сайд-чейн используется не только на басу.
И многие новички об этом даже не подозревают
👨💻В коротком видео Иван показывает какие еще есть способы использовать эту технику, чтобы создать пространство не только для вашего кика.
🔗 Production-сессия → переходите по ссылке
Сегодня стартует набор в новый поток курса «Production»
За 3,5 месяца – путь от первых действий в Ableton до готового трека, который можно выпустить на площадках. Не только «изучить программу», а собрать музыку до конкретного результата.
Что внутри? [Раскрой] 👇
— 48+ занятий в прямых эфирах, по порядку: от первого касания DAW до сведения и мастеринга. Записи остаются у вас навсегда.
— Весь процесс создания трека – …
Что на самом деле означает слово indie? 🗣
Это короткий отрывок из нашего нового видео про Indie Dance, уже смотрели? Тут Иван рассказал, откуда появился термин indie, что он изначально означал и как со временем приобрёл новое значение в музыкальной культуре.
Если ещё не смотрели, в полной версии видео мы разбираем, как создавать музыку в духе представителей сцены Maccabi House. Это полезный формат для тех, кто хоче…
🎛 Как написать Indie Dance в Ableton (Mita Gami, Adam Ten, OMRI, Rafael) | RMA
А вот и обещанное видео:) Maccabi House – один из лейблов, по звучанию которого легко узнать современный Indie Dance.
В новом видео Иван разбирает, из чего складывается этот саунд, а затем собирает трек с нуля в Ableton, повторяя ключевые приемы и характерные элементы направления.
В результате – готовый трек в духе современной Indie Dan…
Совсем скоро выйдет новое видео нашей рубрики с разборами музыкальных стилей.
Если пропустили прошлый выпуск про UK House – обязательно посмотрите. Трек получился очень удачным, а Ableton-проект уже ждёт вас в описании.
Мы очень стараемся над созданием этих роликов, поэтому будем признательны вашим реакциям и комментариям, это поможет в продвижении🙏
А пока попробуйте угадать, какой стиль разберём следующим 👀
И пи…
🟩 Acid-паттерн за 3 клика.
Как-то на эфире, ещё до основной темы, Иван показал простой способ собирать эйсид звук на двух бесплатных плагинах от iftah, которые ему в последнее время особенно зашли – Sting 2 и Slippery Slope.
Показал вроде между делом, а мы сразу попросили записать про это отдельно. Подробнее об этих плагинах для Ableton в этом видео.
⚡️ Застрял в своём звуке? Разберём лично на бесплатной productio…
💡Как сделать ударные более яркими?
Есть и другие способы кроме обработок. Дополнительные слои, короткие акценты и грамотно выстроенные подводящие сэмплы могут заметно усилить ощущение удара и сделать драм-секцию более выразительной. Подробнее в видео.
А если хотите разобрать свой трек — приходите на Production-сессию: найдём, что мешает ему звучать лучше, и определим следующие шаги.
🔗Записаться на Production-сесси
🎛 Как устроен UK House: разбор PROSPA + трек с нуля в Ableton
Жирный бас, стабы, вокальные нарезки и грув, от которого сложно оторваться. PROSPA — одни из тех, кто сделал это звучание визитной карточкой направления.
В конце нового видео на экране готовый трек в духе новой британской клубной сцены. А по пути — весь процесс: Иван разбирает, из чего складывается этот звук, и собирает его в Ableton у нас на глазах.
Сп…
🔥13❤10👍10👏3custom 53347778647493371142
Showing the 12 most recent of 18 posts we hold for @resonance_music_academy. View and reaction counts are the latest single reading for each post, not a live figure, and a recent post is still accumulating both. A view count marked ≈ was rounded by Telegram before we ever saw it — t.me prints views in full below 1,000 and to three significant figures above, so ≈1,200,000 means somewhere between 1,150,000 and 1,249,999. Unmarked counts are exact. Text is reproduced from the public post preview and truncated for length.
Stars beside a post are paid reactions — Telegram Stars, bought with money and spent on that post. They are a different unit from reactions and are never added to them, here or anywhere else on this page.
Polls
The poll we hold for this entry, as Telegram rendered it when we read the post. A poll’s figures keep moving after that, so each one is dated.
Shares as published. No per-option vote count is published by Telegram, so none is shown.
Percentages only — there are no per-option vote counts here, because Telegram publishes none. The public post preview gives each option’s share and a single voter total, and nothing else. Multiplying one by the other would produce a per-option tally that looks measured and is not: the shares are rounded to whole numbers before we ever see them. We print what was published and leave the column that does not exist empty.
The shares need not add up to 100. Rounding alone puts many polls at 99 or 101. A poll that allows more than one answer per voter runs well past 100 by design, and several here do. The bars are drawn against a fixed 100% track at each option’s own percentage rather than normalised to the total, so a poll that exceeds it shows that it does instead of being quietly rescaled.
Read from the 18 most recent posts we hold, published 10 July 2026 to 11 August 2026. Telegram labels each poll by kind — an anonymous poll, a quiz, a closed set of final results — and that label is reproduced rather than paraphrased.
Forward network
Republished by
Channels on the register that have forwarded this channel's posts into their own feed.
Built only from forwarded posts we have actually read, on both sides. Coverage is early and deliberately incomplete: a missing link means we have not read the post that would prove it, never that the relationship does not exist. Counts are distinct forwarded posts observed, so they only ever go up as we read more.
Mentions
Named by 1 registered channel — every channel on the register whose own posts have named this one, by its current username or any other username it currently holds, merged from two separately captured readings of the same fact so a namer caught by only one of them is not missed and a namer both caught is not counted twice. A username this channel has since dropped is not matched — that handle may belong to someone else now, and crediting today’s namer to yesterday’s owner would misattribute it.
Named by
Channels on the register whose posts name this channel's handle.
A mention is a weaker signal than a forward and is counted separately for that reason — naming a channel is not republishing it, and a handle in a post body is easy to place deliberately. The post counts beside each row below are distinct posts in which the handle appeared, from posts we have read on both sides — the “Named by N registered channels” figure above is a different count, of distinct NAMING CHANNELS rather than posts, and is not the sum of the rows under it.
Cite this entry
A live page changes as we take new readings, so a citation should name the measurement it is based on, not just the URL. The line below cites the subscriber count as measured 17 September 2026 — this
entry's latest reading, not the date you are reading this.
“Resonance Music Academy” (@resonance_music_academy), 5,298 subscribers as measured 17 September 2026. Telegram Register, tgregister.com/channel/resonance_music_academy.
Full measurement history, CC BY 4.0. Every reading this register holds for this entry, not just the latest one, as a dated, downloadable record: CSV · JSON. Free to use with attribution to tgregister.com. Each file carries its own generation timestamp, which is the figure to cite for exactly when the data was retrieved.