著者

壹岐 将也 金城 寛 大城 尚紀

出版者

信号処理学会

雑誌

Journal of Signal Processing (ISSN:13426230)

巻号頁・発行日

vol.17, no.3, pp.81-86, 2013-05-25 (Released:2013-05-25)

参考文献数

10

被引用文献数

1

---

This paper presents a method of maturity detection of the tropical fruits using a smell sensor. We investigate many sensing data of different fruits and find out that the data of the fruits are characterized as a first-order lag element. The first-order lag element has two parameters: gain and time constant. Knowing the gain and time constant of the smell data is useful for detecting the maturity of the fruits. In this paper, we apply a genetic algorithm to identify the gain and time constant parameters for the sensing data. Experiments of the maturity detection for monkey bananas and guavas show good results.

著者

矢野 和洞 鈴木 丈裕 鈴木 智也

出版者

Research Institute of Signal Processing, Japan

雑誌

Journal of Signal Processing (ISSN:13426230)

巻号頁・発行日

vol.24, no.3, pp.113-122, 2020-05-15 (Released:2020-05-15)

参考文献数

10

---

Foreign-exchange (FX) brokers have some risk factors such as price fluctuation risk and latency of data transmission. To reduce these risks in FX brokerage services, we propose a short-term prediction of exchange rates quoted by counter-party banks. We consider that these exchange rates are generated by the knowledge of each counter-party bank, and therefore try to extract the knowledge by using a machine learning method. As a result, we could predict the direction of exchange rates with a prediction accuracy of about 80% if the prediction interval is 100[ms]. Furthermore, by integrating the knowledge of counterparty banks by the ensemble learning, we could improve not only prediction accuracy but also profitability of foreign-exchange brokers. These improvements can be considered as an effect of collective knowledge based on the diversity prediction theorem, but this effect might be limited by extremely short-term prediction of foreign-exchange rates after 100[ms]~200[ms].

著者

Naoya Murashima Hirokazu Kameoka Li Li Shogo Seki Shoji Makino

出版者

Research Institute of Signal Processing, Japan

雑誌

Journal of Signal Processing (ISSN:13426230)

巻号頁・発行日

vol.25, no.4, pp.145-149, 2021-07-01 (Released:2021-07-01)

参考文献数

24

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This paper deals with single-channel speaker-dependent speech separation. While discriminative approaches using deep neural networks (DNNs) have recently proved powerful, generative approaches, including methods based on non-negative matrix factorization (NMF), are still attractive because of their flexibility in handling the mismatch between training and test conditions. Although NMF-based methods work reasonably well for particular sound sources, one limitation is that they can fail to work for sources with spectrograms that do not comply with the NMF model. To address this problem, attempts have recently been made to replace the NMF model with DNNs. With a similar motivation to these attempts, we propose in this paper a variational autoencoder (VAE)-based monaural source separation (VASS) method using a conditional VAE (CVAE) for source spectrogram modeling. We further propose an extension of the VASS method, called the discriminative VASS (DVASS) method, which uses a discriminative criterion for model training so that the separated signals directly become optimal. Experimental results revealed that the VASS method performed better than an NMF-based method, and the DVASS method performed better than the VASS method.

著者

He He Jun-Han Wang Shun Kojima Kazuki Maruta Chang-Jun Ahn

出版者

Research Institute of Signal Processing, Japan

雑誌

Journal of Signal Processing (ISSN:13426230)

巻号頁・発行日

vol.27, no.3, pp.49-57, 2023-05-01 (Released:2023-05-01)

参考文献数

16

被引用文献数

1

---

In a high-speed moving mobile environment, the channel state information (CSI) in the last part of the packet is different from the actual channel in the beginning part. Therefore, the channel estimation accuracy is degraded, especially when a small number of pilot symbols are used to ensure transmission efficiency. For the above reasons, it is necessary to compensate for CSIs to achieve reliable communication. Decision feedback channel estimation (DFCE) has been widely considered to be one of the channel tracking methods. However, the presence of time and frequency selective fading environments still causes estimation errors due to the decision-making process. We focused on the time-frequency domain response of the CSIs, which can be represented as a two-dimensional image. This paper newly proposes a regression convolutional neural network (CNN) based channel tracking scheme using the time-frequency domain response of the CSIs by DFCE for training and prediction to solve these problems. Computer simulation results demonstrate that the proposed scheme can achieve higher BER performance than the conventional schemes.

著者

鵜木 祐史

出版者

信号処理学会

雑誌

信号処理 (ISSN:13426230)

巻号頁・発行日

vol.12, no.5, pp.339-348, 2008-09

被引用文献数

4

---

私達は,日常,何不自由なく音声を介してコミュニケーションをとっている。しかし,読者はこんな経験をしたことはないだろうか。例えば,お風呂場や教会など音が非常に響く環境(残響環境)や,人で賑わっている雑多な場所,交通量の多い場所といった非常に騒がしい環境(騒音環境)では,静寂な環境に比べて非常に音を聴き取り難く,いつもと同じように簡単に会話をできないと感じたことである。これは,身の回りの音場環境の影響により,音声が歪んだため,音声知覚に重要な情報が欠落したことによるものである。このような音声コミュニケーションの難しさを評価する尺度として,音声明瞭度,単語・文章了解度が利用されている。前者は無意味音節を発声したとき受聴者がその何%を正しく聞き取れたかを,後者は沢山の有意味単語を発声したとき受聴者が正しく聞き取れた単語数の割合を示すものである。これらの尺度は,音声情報伝達を議論するときに,よく利用されるものであるが,同時に室内音饗学と関係して議論されるとき,音声レベル,騒音レベル,残響時間等の物理量との関連を見出そうとする検討も古くから行われている。代表的なものとして,Houtgast とSteeneken によって提唱された変調伝達関数(Modulation Transfer Function:MTF)に基づく音声明瞭度予測理論がある。これは,音場内において,音声波形の時間的な包絡線情報(以後,エンベロープと呼ぶ)が残響や雑音によって変形することに着目し,100%振幅変調した正弦波を利用してMTFの減衰量から音声伝達指標(SpeechTransmission Index: STI)を予測するものである。この方法は,その後,簡易測定法であるRASTIとして提案され,現在でも標準的な方法として利用されている。STI/RASTI の方法は,理論的に明解であり,実用上多くの利点をもつため,講演会場など室内音響設計にも役立っている。しかしながら,この方法は決して万能であるわけではなく,(1) 音場の時間構造・空間構造を反映していないことや(2) 音源(音声)の物理特性を反映していないことから,音声明瞭度予測に対して適用限界があることが示唆されている。Houtgast とSteeneken が提唱した音声明瞭度予測理論は,室内音響を拡散音場と仮定しているため,上記のように,その適用限界があることは間違いない。しかしながら,室内音響伝達系を入出力の強度情報の関係と残響・雑音に対するMTF を明解に関係づけた点は,大きな業績であり,評価されることであろう。また,この考えは,他の音声信号処理で残されている諸問題を解決するために利用することもできる。例えば,室内の残響の影響を受けた音声を伝達系を測定せずに回復する方法 や,残響環境下での音声の基本周波数推定方法がある。最近では,室内の残響時間をブラインド推定する方法や異なる二つの音場空間を考慮した音場再生法も提案されている。本論文は,合計3回のシリーズで構成される。これらでは,著者が関係した研究分野(残響環境下の音声信号処理)を中心に,MTF を利用した音声信号処理を解説する。本稿では,まず,Houtgast とSteeneken が示したMTF の概念を解説するとともに,その概念に基づいたパワーエンベロープ逆フィルタ法を紹介する。

著者

Zhi Zhu Katsuhiko Yamamoto Masashi Unoki Naofumi Aoki

出版者

信号処理学会

雑誌

Journal of Signal Processing (ISSN:13426230)

巻号頁・発行日

vol.18, no.6, pp.303-307, 2014-11-25 (Released:2014-11-25)

参考文献数

7

---

Speech scrambling aims to eliminate intelligibility of original speech in order to preventing eavesdropping and copyright infringement. There is, however, a problem in that completely recovering scrambled speech into the original speech cannot be achieved with conventional methods. In this paper, we propose a speech scrambling method that uses the random-bit-shift of quantization bits with common keys. We evaluated the confidentiality and efficiency of the proposed method by using two objective measures, SER and PESQ. As a result we confirmed that speech signals can be scrambled into completely unintelligible sounds with the proposed method. Moreover, it is possible to restore a scrambled speech signal into the original one completely. In addition, we also confirmed that the scrambled speech signal could not be descrambled correctly with the wrong key.

著者

Chisato Takahashi Kenya Jin'no

出版者

Research Institute of Signal Processing, Japan

雑誌

Journal of Signal Processing (ISSN:13426230)

巻号頁・発行日

vol.27, no.4, pp.65-68, 2023-07-01 (Released:2023-07-01)

参考文献数

5

---

Neural Architecture Search (NAS), which aims to automatically optimize the structure of a neural network for achieving excellent classification performance, has attracted considerable attention in recent years. Recently, zero-shot evaluation methods have been proposed for estimating classification performance without training to reduce the search time. However, these indices are still insufficient for finding the best-performing neural networks. In this study, we demonstrate that it is possible to evaluate convolutional neural networks (CNNs) using the robustness of the rectified linear unit (ReLU) output distribution to weights. We propose a new zero-shot CNN evaluation index based on this robustness index.

著者

Riki Watabe Hiroyuki Kamata

出版者

Research Institute of Signal Processing, Japan

雑誌

Journal of Signal Processing (ISSN:13426230)

巻号頁・発行日

vol.25, no.6, pp.227-231, 2021-11-01 (Released:2021-11-01)

参考文献数

8

---

In this paper, we propose a novel method for estimating the time delay in chaotic time series analysis. In recent years, focusing on the shape of an attractor using persistent homology has attracted attention. However, this method has a problem in that the calculation cost is enormous. In the proposed method, we aim to improve the calculation speed while considering the geometric shape of the attractor by focusing on the distance between the points in the data group.

著者

Reda Elbarougy Bagus Tris Atmaja Masato Akagi

出版者

Research Institute of Signal Processing, Japan

雑誌

Journal of Signal Processing (ISSN:13426230)

巻号頁・発行日

vol.24, no.6, pp.229-235, 2020-11-01 (Released:2020-11-01)

参考文献数

23

---

Speech and visual information are the most dominant modalities for a human to perceive emotion. A method of recognizing human emotion from these modalities is proposed by utilizing feature selection and long short-term memory (LSTM) neural networks. A feature selection method based on support vector regression is used to select the relevant features among thousands of features extended from speech and video features via bag-of-X-words. The LSTM neural networks then are trained using a number of selected features and also separately optimized for every emotion dimension. Instead of utterance-level emotion recognition, time-frame-based processing is performed to enable continuous emotion recognition using a database labeled for each time frame. Experimental results reveal that a system with feature selection is more effective for predicting emotion dimensions for a single language than the baseline system without feature selection. The performance is measured in terms of the concordance correlation coefficient obtained by averaging the valence, arousal, and liking dimensions.

著者

渡部 和

出版者

〔信号処理学会〕

雑誌

信号処理 (ISSN:13426230)

巻号頁・発行日

vol.9, no.5, pp.363-380, 2005-09

被引用文献数

5

著者

渡部 和

出版者

〔信号処理学会〕

雑誌

信号処理 (ISSN:13426230)

巻号頁・発行日

vol.9, no.4, pp.285-294, 2005-07

出版者

信号処理学会

雑誌

Journal of Signal Processing (ISSN:13426230)

巻号頁・発行日

vol.24, no.3, pp.129-130, 2020-05-15 (Released:2020-05-15)

著者

Takahiro Komai Song-Ju Kim Takuji Kousaka Hiroaki Kurokawa

出版者

Research Institute of Signal Processing, Japan

雑誌

Journal of Signal Processing (ISSN:13426230)

巻号頁・発行日

vol.23, no.4, pp.177-180, 2019-07-20 (Released:2019-07-20)

参考文献数

5

被引用文献数

2

---

In our previous studies, we showed that the estimation of the rock-scissors-paper (RSP, janken) game strategy is effective for the prediction of a player's hand sign sequences. The purpose of this study is to propose a method to estimate the RSP game strategy in the basis of human personality in an RSP game. To estimate a player's strategy in the RSP game, it is effective to compare the player's hand sign sequence and the hand sign sequences given by various typical RSP strategies on the basis of similarity. In this study, we propose the method of using a homology search to calculate the similarity between sequences. The results show that our proposed method is effective for strategy estimation.

著者

Yuki Hoshino Kenya Jin'no

出版者

Research Institute of Signal Processing, Japan

雑誌

Journal of Signal Processing (ISSN:13426230)

巻号頁・発行日

vol.22, no.4, pp.153-156, 2018-07-25 (Released:2018-07-25)

参考文献数

15

被引用文献数

1

---

Recently, machine learning has been attracting attention. Machine learning is mainly realized by the learning of artificial neural networks. Various learning methods have been proposed; however, the learning methods are based on gradient methods. On the other hand, swarm intelligence (SI) algorithms have been attracting attention in the optimization field. Generally speaking, SI algorithms have a large computation cost. Therefore, there are few cases of SI algorithms being applied to machine learning. In this paper, we propose a novel learning algorithm for an artificial neural network which applies our proposed nonlinear map optimization (NMO) method. NMO consists of some simple particles which are driven by a simple nonlinear map. NMO can be classified as an SI algorithm. However, it has only a small computation cost. Therefore, NMO can be applied to a learning algorithm for an artificial neural network. In this paper, we introduce NMO, and a small learning simulation is carried out to confirm the performance of our learning method.

著者

辻 広生 福水 洋平 道関 隆国 山内 寛紀

出版者

Research Institute of Signal Processing, Japan

雑誌

Journal of Signal Processing (ISSN:13426230)

巻号頁・発行日

vol.22, no.3, pp.121-134, 2018-05-25 (Released:2018-05-25)

参考文献数

13

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We propose a multistructure convolutional neural network (CNN) for hiragana recognition of remarkably degraded license plate images captured by security cameras for the purpose of criminal investigation. The proposed multistructure CNN can use the optimal resolution image that cannot be used by conventional CNN by processing multiresolution images so that the recognition performance is improved. In many cases, plural candidates are allowed in remarkably degraded license plate character recognition for criminal investigation because it is not realistic to achieve practical level correct rate with a single candidate. The general criterion of practical level recognition accuracy for criminal investigation is whether the method achieves the correct rate of 90 percent by allowing up to the second candidate. Generally, the recognition accuracy of CNN decreases when the degradation estimation is inaccurate, and the CNN is not optimized. Under the condition that the CNN was not optimized, the proposed multistructure CNN could achieve practical level recognition performance while the conventional CNN could not achieve that performance.

著者

Katsuhiko Yamamoto Zhi Zhu Masashi Unoki Naofumi Aoki

出版者

信号処理学会

雑誌

Journal of Signal Processing (ISSN:13426230)

巻号頁・発行日

vol.18, no.4, pp.205-208, 2014-07-30 (Released:2014-07-30)

参考文献数

10

---

Speech scrambling methods are widely used for copyright protection and encrypting digital speech signals in order to guarantee the confidentiality of the original signals. They are very important methods for preventing eavesdropping and unauthorized copying. However, it seems to be impossible to completely recover a scrambled speech signal into the original signal. Moreover, nobody can comprehend the partial speech content from speech signals scrambled with these methods. In this paper, we propose a semi-scramble method for speech signals based on phonemic restoration. By using a speech scrambling method based on the random-bit shift of quantization bits, speech signals are converted to scrambled signals in partial intervals. We evaluated the confidentiality and efficiency of the proposed method by using two objective measures, signal-to-error ratio (SER) and perceptual evaluation of speech quality (PESQ). As a result, we confirmed that the proposed method can play a role in copyright protection for an original signal and recover a semi-scrambled speech signal into the original one. Finally, we indicated that the acoustic characteristics of signal semi-scrambled with the proposed method enable the listener to understand the speech information.

著者

長谷川 弘 木下 健太郎 岸田 悟

出版者

信号処理学会

雑誌

Journal of Signal Processing (ISSN:13426230)

巻号頁・発行日

vol.18, no.1, pp.29-38, 2014-01-25 (Released:2014-01-25)

参考文献数

26

被引用文献数

1

---

We construct a speaker authentication system, where 3-layerd neural networks with ensemble learning algorithm are used, and investigate the effect of ensemble learning on the performance of the system. From the results, we found that the authentication rates of the system for a person became to 100% by using ensemble learning. Therefore, the new ensemble leaning used in this study is thought to be useful for the speaker authentication system with layered neural networks. In addition, a new multi-step authentication system for many persons by extending the system for a person was suggested. In the system, the ensemble learning was also useful for the speaker authentication system of neural networks for many persons.