You will be shown an excerpt from a computer science scientific research paper, followed by a question about the paper. Please answer the question. Do not include any text in your response other than the answer.

Context: In the Time2Note procedure, we add the scaled positional embedding w T to e (S) T . Then, we transfer it to the notewise embedding e (S) N with average pooling by an alignment matrix M ∈ { 0 , 1 } T × N as (2), where M indicates the alignment path between a piano roll and a series of notes. This process enables each frame of the notewise embedding to preserve the information of the original note duration : However, conventional Transformer-based studies encoded music as a series of musical events [15]. Using event-based representations differs from how humans perceive a rendered or score-written melody for harmonization [16]. Instead, a grid-based melody representation can be more intuitive for modeling melodic patterns synchronized with chord labels [4], [17], [18]. In our work, we convert a melody into a more intuitive note-based representation, where each frame represents one note. To this end, we use a novel time-to-note compression method to map a binary piano roll representation into a note-based embedding.

Question: Is TimeToNote method truly a novel idea to capture a musical hierarchy? It seems to be just a simple trick that also have been used in one of the previous music generation studies (MuseMorphose, 2021).
TimeToNote method is different from similar approaches to capture musical hierarchy. First, it aims to aggregate grid-based information into musically meaningful units, while previous approaches map low-level musical units to high-level musical units, such as a bar. Moreover, the aggregated information preserves the length information of the original representation, which is also different from the previous studies that simply average-pooled the representation.