Analyze a song
do words, tone, and feel.
Speak AI runs AI song analysis on every track: the lyrics transcribed, the tone and emotion in the vocal delivery, and the themes and structure pulled into notes you can actually write from. We build it with you.
Wygrane, które zespoły wdrażają.
Czas do działającego produktu, godziny zaoszczędzane na plik i zaoszczędzane dolary. Ta sama platforma, zupełnie inne zastosowania.
Firma zajmująca się technologią prawną buduje platformę white-label do przesłuchań 8 miesięcy szybciej.
Globalna agencja badawcza uruchamia platformę badań jakościowych white-label.
Firma zajmująca się inteligentnością prawną przetwarza 5100+ godzin rozmów przewoźników 95% szybciej.
Firma doradcza w służbie zdrowia skróciła przetwarzanie sesji z 8 godzin do 0,3.
Producent e-commerce scentralizował przegląd rozmów i zmniejszył go o 85%.
Firma rekrutacyjna skraca czas raportu kandydata z 5 godzin do 10 minut.
Bring a song. Leave with it analyzed.
Sesja robocza, a nie prezentacja handlowa. Bez zobowiązań.
You bring a real track
A song you’re reviewing, studying, writing about, or pitching. Whatever you’d normally listen through by hand.
We map what you’re looking for
The themes, structure, and mood cues that matter for your review, assignment, or pitch. Your words, your framework.
Widzisz to analizowane na żywo
Your own track, transcribed and broken down on your criteria, with notes you can build a review or analysis on.
Song analysis for every kind of listener.
The same engine, pointed at whatever track you’re working through.
Song analysis for class
Break down an assigned track into lyrics, structure, and theme in minutes, with a transcript and notes a discussion or essay can build on.
Reviews & features
Transcribe interviews and lyric breakdowns fast, then pull the exact lines and quotes a review or feature needs without replaying a track five times.
Songwriters & producers
Compare drafts and takes on structure, rhyme, and vocal delivery, so revisions target the section that is actually losing the listener.
Reaction & breakdown content
Turn a first listen into a scripted breakdown video or post, with themes, standout lines, and mood shifts already pulled out.
Music therapy sessions
Analyze the songs a client brings in for tone, emotional arc, and recurring themes, building a record you can track across sessions.
Sync & licensing review
Score a catalog on mood, energy, and theme at scale, so pitching the right track for a scene or campaign takes minutes.
A different approach to song analysis.
Song analysis is the process of breaking a track into its component parts, lyrics, melody, structure, and instrumentation, to understand its meaning, its mood, and how it lands on a listener. Marketers, researchers, educators, and music writers have used it for years to understand what a song communicates and why it works, and to make better decisions about the pieces they write about, teach, license, or pitch.
Why song analysis breaks down
For most people, analyzing a song by ear means the same slow loop: replay the track, pause to catch a line, rewind because you missed the bridge, and try to hold the whole shape of it in your head at once. Lyrics get copied from a fan site that got a word wrong. The emotional turn in the vocal, the moment the delivery gets quieter or the energy spikes, never makes it into the notes at all, because that part never had text to grab onto.
Reading the song, not just the words
Speak AI treats a song the way a trained ear would, at machine speed. The track is transcribed in your language, with 100+ supported, and then the recording itself is analyzed: the tone and energy in the vocal delivery, the mood shifts between verse and chorus, the moments where the performance pushes harder or pulls back. Sections, verse, chorus, bridge, outro, are identified and labeled, and recurring words, images, and themes are pulled into structured notes you can use directly.
Then the questions start. Ask across a track, an album, or an entire catalog with AI chat, using the same close-reading workflow a lyrics class or a music blog would do by hand, now running natively over the recording with ChatGPT, Claude, and Gemini built in.
What people ask about a song
- “What is this song actually about, and where does the lyric say it most directly?”
- “Which lines carry the emotional peak, and how does the vocal delivery change there?”
- “What themes or images recur across the verses, and where do they first appear?”
- “How does the melody and instrumentation support what the lyrics are saying?”
- “Where does the mood shift between sections, and what causes the shift?”
From a replayed track to a finished breakdown
The result is a first draft of the analysis instead of a blank page. A class assignment starts with the structure and themes already pulled out. A review starts with the exact quote and timestamp instead of a half-remembered line. And because a single song rarely stands alone, Panele sterowania, które możesz dostosować i oznakować własną marką track theme, tone, and structure across an artist’s catalog over time, so this album is measured against the last one instead of just described from memory. One legal intelligence firm put a very different kind of audio, 5,100+ hours of carrier calls, through the same underlying engine and saved 700K+ across a five-figure hour volume, which is the same scale of listening and tagging a song catalog runs on, just pointed at a different kind of recording.
And because a track is rarely the only thing you are working through, the same engine that reads a song’s tone and structure also scores calls and coaches conversations, connecting a lyric breakdown to ocena rozmów oraz coaching on the same platform.
Zaprojektowane z Tobą, dokładne od pierwszego dnia.
A generic AI tool starts from zero. We shape the fields, tags, and prompts around how you actually analyze songs, whether that is a class assignment, a review, or a catalog pitch, then prime the workspace on tracks you already know so it is useful from the first file. You get structured notes back, not just a transcript.
- Projektujemy kontekst, pola i punktacja around how you actually analyze songs, not a template.
- Your reference tracks and past breakdowns prime the baza wiedzy przed wdrożeniem.
- Structured data on every song, queryable from Claude, ChatGPT, and Cursor through the serwer MCP.
Przenieś swoje aplikacje do Claude, ChatGPT i Cursor.
Bez terminala. Bez npm. Bez konfiguracji. Serwer MCP Speak AI zapewnia dowolny asystent 100+ narzędzi szukać, analizować i działać na podstawie Twojej bazy wiedzy w około 60 sekund. To ta sama warstwa, na której działają Twoje aplikacje, połączona z setkami aplikacji w Twoim stosie poprzez warstwę integracji i pełne API dla deweloperów.
Jeden system rejestracji dla wszystkiego, co mówi Twój zespół.
Osobiście i wirtualnie, w jednym miejscu. Bez łączenia razem narzędzia do spotkań, rejestratora głosu i trzech innych aplikacji. Speak AI przechwytuje to wszystko do jednej przeszukiwalnej bazy wiedzy, na której zbudowane są Twoje aplikacje.
Zespoły rozwijają się na Speak AI.
Rzeczywiste opinie od zespołów używających Speak AI do badań, transkrypcji, spotkań i pracy klientów.
Pytania, które otrzymujemy
Twoja pierwsza karta wyników jest uruchamiana na rzeczywistym nagraniu podczas konsultacji. Wdrożenie zespołu trwa dni, a nie miesiące, ponieważ budujemy to z Tobą i uruchamiamy na Twoich istniejących nagraniach.
Zgromadzone użytkowanie, a nie za miejsce, bez minimalnych wolumenów. Piloty są w pełni kredytowane. Dostosowujemy ceny do Twojego dokładnego przepływu pracy podczas rozmowy.
Speak AI obsługuje ponad 100 języków, w tym rozmowy, które zmieniają język w środku zdania, i może tłumaczyć na wejściu i wyjściu.
Tak. Wdrożenia white-label działają w Twojej własnej domenie z Twoim logo, w tym platformy klienckie, które agencje odsprzedają, plus oznaczone aplikacje iOS i Android.
Song analysis breaks a track into its parts, lyrics, melody, structure, and instrumentation, to understand what it communicates and how. Speak AI automates the first pass: transcribing the words, reading the tone and energy in the vocal delivery, and surfacing the themes and structure so you can build from there instead of starting from a blank page.
Any song with a clear narrative or emotional arc works well: a verse-chorus structure with a shift in tone, a bridge that changes the story, or lyrics that build in intensity. Speak AI works the same way across genres, so the best song to analyze is usually the one you already have questions about.
That is a matter of taste, not something Speak AI scores for you. What the platform can do is transcribe and analyze any track, YungBlud’s catalog included, so you can compare themes, energy, and delivery across songs and form your own answer with the data in front of you.
ChatGPT can discuss lyrics you paste in, but it cannot listen to the audio itself. Speak AI transcribes the actual recording, reads tone, energy, and delivery from the audio, and then lets you ask ChatGPT, Claude, or Gemini questions across that transcript and analysis, so you get audio-aware answers instead of guesses from text alone.
Enterprise obejmuje obsługę BAA, niestandardowe umowy przetwarzania danych, SSO i opcje rezydencji danych. Udostępniamy dokumentację zabezpieczeń na żądanie i dostosowujemy każdą kompilację do Twoich wymagań.
From a first listen to a finished analysis.
Book a free consult, bring a real song, and watch it transcribed, broken down, and ready to write from before the meeting ends. Consults include early access to new features, an extended trial, and implementation credits.