JP2020112683A - 音響解析方法および音響解析装置 - Google Patents
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Abstract
Description
図1は、本発明の第1実施形態に係る音響解析装置100の構成を例示するブロック図である。音響解析装置100は、楽曲の歌唱音または演奏音等の音響を表す音響信号Vを解析することで、当該楽曲の調を推定する情報処理装置である。音響解析装置100は、複数の主音(具体的には平均律の12半音)と調名(長調および短調)との組合せに相当する24種類の調を候補として音響信号Vから何れかの調を推定する。なお、調の種類数は、24種類に限定されない。
具体的には、調推定モデル22は、特徴量Yの時系列の入力により、調を表す情報(以下「調情報H」という)を生成する。
本発明の第2実施形態を説明する。なお、以下の各例示において機能が第1実施形態と同様である要素については、第1実施形態の説明で使用した符号を流用して各々の詳細な説明を適宜に省略する。
楽曲のコードと調とは相関関係がある。例えば、楽曲の調の音階を構成音とするコードが当該楽曲内で演奏される。特に、楽曲において特定の調が設定された区間の先頭のコードは、当該調の主音を根音とするコードと一致する可能性が高いという傾向がある。第3実施形態では、以上の傾向をもとに第1実施形態で推定された調を修正する。
以上に例示した各態様に付加される具体的な変形の態様を以下に例示する。以下の例示から任意に選択された複数の態様を、相互に矛盾しない範囲で適宜に併合してもよい。
Claims (8)
- 音響信号の特徴量の時系列と調との関係を学習した学習済モデルに、音響信号の特徴量の時系列を入力することで、調を表す調情報を生成する
コンピュータにより実現される音響解析方法。 - 同じコードが継続する継続区間毎に前記音響信号の特徴量を前記学習済モデルに入力することで、当該継続区間毎に前記調情報を生成する
請求項1の音響解析方法。 - 各継続区間の前記特徴量は、前記音響信号のうち音階音に対応する成分強度における当該継続区間の時間変化に関する指標を音階音毎に含む
請求項2の音響解析方法。 - 前記特徴量は、前記音響信号のうち音階音に対応する成分強度を複数のオクターブにわたり加算した成分強度を音階音毎に含む
請求項1の音響解析方法。 - 前記調情報が表す調が連続する調区間の時間長が所定値を下回る場合に、当該調区間の調を、当該調区間の直前または直後の調情報が表す調に置換する
請求項1から請求項4の音響解析方法。 - 音響信号におけるコードの時系列に応じて、前記調情報が表す調が連続する調区間の端点を変更する
請求項1から請求項5の音響解析方法。 - 前記調区間の始点を含む探索区間における音響信号のコードの時系列に、当該調区間の調情報が表す調の主音を根音とするコードがある場合に、当該調区間の始点を、当該コードに対応する区間の始点に変更する
請求項6の音響解析方法。 - 音響信号の特徴量の時系列と調との関係を学習した学習済モデルであって、音響信号の特徴量の時系列の入力から、調を表す調情報を生成する調推定モデル
を具備する音響解析装置。
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JP2019003324A JP7375302B2 (ja) | 2019-01-11 | 2019-01-11 | 音響解析方法、音響解析装置およびプログラム |
CN202080007107.2A CN113196381B (zh) | 2019-01-11 | 2020-01-09 | 音响解析方法以及音响解析装置 |
PCT/JP2020/000374 WO2020145326A1 (ja) | 2019-01-11 | 2020-01-09 | 音響解析方法および音響解析装置 |
US17/331,520 US12014705B2 (en) | 2019-01-11 | 2021-05-26 | Audio analysis method and audio analysis device |
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CN117043852A (zh) * | 2021-03-26 | 2023-11-10 | 雅马哈株式会社 | 和弦推定装置、训练装置、和弦推定方法及训练方法 |
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JP2018141899A (ja) * | 2017-02-28 | 2018-09-13 | 株式会社Nttドコモ | 楽器音認識装置及び楽器音認識プログラム |
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US7842878B2 (en) * | 2007-06-20 | 2010-11-30 | Mixed In Key, Llc | System and method for predicting musical keys from an audio source representing a musical composition |
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